TESTING A MODEL OF CAREER INDECISION AMONG UNIVERSITY
STUDENTS BASED ON SOCIAL COGNITIVE CAREER THEORY
A THESIS SUBMITTED TO
THE GRADUATE SCHOOL OF SOCIAL SCIENCES
OF
MIDDLE EAST TECHNICAL UNIVERSITY
BY
AYġENUR BÜYÜKGÖZE KAVAS
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR
THE DEGREE OF DOCTOR OF PHILOSOPHY
IN
THE DEPARTMENT OF EDUCATIONAL SCIENCES
MAY 2011
Approval of the Graduate School of Social Sciences
Prof. Dr. Meliha AltunıĢık
Director
I certify that this thesis satisfies all the requirements as a thesis for the degree of
Doctor of Philosophy.
Prof. Dr. Ali Yıldırım
Head of Department
This is to certify that we have read this thesis and that in our opinion it is fully
adequate, in scope and quality, as a thesis for the degree of Doctor of Philosophy.
Assoc. Prof. Dr. Oya Yerin Güneri
Supervisor
Examining Committee Members
Prof. Dr. Ayhan Demir (METU, EDS)
Assoc. Prof. Dr. Oya Yerin Güneri (METU, EDS)
Assoc. Prof. Dr. Feride Bacanlı (GU, EDS)
Assoc. Prof. Dr. Özgür Erdur Baker (METU, EDS)
Assist. Prof. Dr. Zeynep Hatipoğlu Sümer (METU, EDS)
iii
PLAGIARISM
I hereby declare that all information in this document has been obtained and
presented in accordance with academic rules and ethical conduct. I also declare
that, as required by these rules and conduct, I have fully cited and referenced
all material and results that are not original to this work.
Name, Last name : AyĢenur Büyükgöze Kavas
Signature :
iv
ABSTRACT
TESTING A MODEL OF CAREER INDECISION AMONG UNIVERSITY
STUDENTS BASED ON SOCIAL COGNITIVE CAREER THEORY
Büyükgöze Kavas, AyĢenur
Ph.D., Department of Educational Sciences
Supervisor: Assoc. Prof. Dr. Oya Yerin Güneri
May 2011, 213 pages
The aim of the current study is to investigate the some potential factors that
contribute to career indecision of university students. In accordance with that, a
mediational causal model based on Social Cognitive Career Theory (SCCT) was
proposed to test; a) the direct and indirect relationships of locus of control, perceived
parental attitudes, career decision-making self-efficacy, and career outcome
expectations with career indecision and b) to what extend the combination of these
variables explain career indecision. The sample of the study was composed of 723
(338 female, 383 male, 2 unspecified) university students. Demographic Information
Form, Career Decision Scale, Career Decision Self-Efficacy Scale Short-Form,
Career Outcome Expectations Scale, Parental Attitudes Scale, and Rotter‟s Internal-
External Locus of Control Scale were used to collect data. Pilot studies were
v
conducted for assessing the psychometric properties of the Turkish version of Career
Decision Scale, Career Decision Self-Efficacy Scale Short Form, and Career
Outcome Expectations Scale. Path analysis was utilized to identify whether the
proposed model of career indecision fit the data.
Results indicated four nonsignificant paths. Therefore, the proposed model was
trimmed by eliminating the nonsignificant paths and adding a new path. Accordingly,
findings revealed that career indecision was negatively predicted from career
decision-making self-efficacy, perceived parental psychological autonomy, and
positively predicted from locus of control and career outcome expectations.
Additionally, locus of control, perceived parental acceptance/ involvement, perceived
parental psychological autonomy, and career decision-making self-efficacy were
indirectly related to career indecision. Overall, the trimmed model supported SCCT
and accounted for 32% of the variance in career indecision.
Keywords: Career Indecision, Career Decision-making Self-efficacy, Career
Outcome Expectations, Social Cognitive Career Theory
vi
ÖZ
SOSYAL BĠLĠġSEL KARĠYER KURAMINA DAYALI BĠR KARĠYER
KARARSIZLIĞI MODELĠNĠN ÜNĠVERSĠTE ÖĞRENCĠLERĠNDE SINANMASI
Büyükgöze Kavas, AyĢenur
Doktora, Eğitim Bilimleri Bölümü
Tez DanıĢmanı: Doç. Dr. Oya Yerin Güneri
Mayıs 2011, 213 sayfa
Bu çalıĢmanın amacı, üniversite öğrencilerinin kariyer kararsızlığını etkileyen bazı
olası faktörleri incelemektir. Bu doğrultuda, kontrol odağı, algılanan anne baba
tutumu, kariyer karar verme öz-yeterliği ve kariyer sonuç beklentileri ile kariyer
kararsızlığı arasındaki doğrudan ve dolaylı iliĢkileri sınamak amacıyla; a) Sosyal
BiliĢsel Kariyer Kuramı‟na (SBKK) dayalı ara değiĢkenli nedensel bir model
önerilmiĢ ve b) tüm bu değiĢkenlerin birleĢiminin kariyer kararsızlığını ne ölçüde
açıkladığı sınanmıĢtır. AraĢtırmanın örneklemini, 723 (338 kız, 383 erkek, 2
belirtilmemiĢ) lisans öğrencisi oluĢmuĢtur. Bu çalıĢmada, KiĢisel Bilgi Formu,
Kariyer Karar Ölçeği, Kariyer Kararı Öz-Yeterlik Ölçeği Kısa Formu, Kariyer Sonuç
Beklentileri Ölçeği, Anne-Baba Tutum Ölçeği ve Rotter'ın Ġç-DıĢ Kontrol Odağı
Ölçeği veri toplama aracı olarak kullanılmıĢtır. Kariyer Karar Ölçeği, Kariyer Kararı
vii
Öz-Yeterlik Ölçeği Kısa Formu, Kariyer Sonuç Beklentileri Ölçeği‟nin Türkçe
formlarının psikometrik özelliklerini değerlendirmek amacıyla pilot çalıĢmalar
yapılmıĢtır. Önerilen kariyer kararsızlık modelininin elde edilen veriye uyup
uymadığını belirlemek için yol analizi kullanılmıĢtır.
Yol analizinin sonuçları önerilen modeldeki dört yolun anlamlı olmadığını
göstermiĢtir. Bu nedenle, anlamlı olmayan yollar önerilen modelden çıkarılmıĢ ve
yeni bir yol eklenerek model tekrar düzenlenmiĢtir. Buna göre, bulgular kariyer karar
verme öz-yeterliğinin ve algılanan anne-baba psikolojik özerkliğinin, kariyer
kararsızlığını olumsuz yönde; kontrol odağı ile kariyer sonuç beklentilerinin ise
olumlu yönde yordadığını göstermiĢtir. Ayrıca, kontrol odağı, algılanan anne-baba
kabul/ ilgi tutumu, algılanan anne-baba psikolojik özerkliği tutumu ve kariyer karar
verme öz-yeterliği, kariyer kararsızlığı ile dolaylı olarak iliĢkilidir. Sonuç olarak,
yeniden düzenlenen model Sosyal BiliĢsel Kariyer Kuramını desteklemekte ve
kariyer kararsızlığına iliĢkin varyansın %32‟sini açıklamaktadır.
Anahtar Kelimeler: Kariyer Kararsızlığı, Kariyer Karar Verme Öz-Yeterliği, Kariyer
Sonuç Beklentileri, Sosyal BiliĢsel Kariyer Kuramı
viii
DEDICATION
To my mother, who instilled in me the value of an education &
To my father, who taught me to work hard and be persevering &
To my husband, who shares the life with me
ix
ACKNOWLEDGMENTS
I would initially like to express my deepest gratitude to my supervisor Assoc. Prof.
Dr. Oya Yerin Güneri, for her guidance, suggestions, and gentle understanding. It
was a fortune to work with her during this challenging process. Indeed, her scientific
perspective, knowledge, ethical considerations, guidance, honesty, understanding,
and encouragement make her an excellent mentor and a genuine model for me.
I would like to express my gratitude to the examining committee members, Prof. Dr.
Ayhan Demir, Assoc. Prof. Dr. Feride Bacanlı, Assoc. Prof. Dr. Özgür Erdur Baker,
and Assist. Prof. Dr. Zeynep Hatipoğlu Sümer for their valuable contributions. I
would also thank them and all my professors for their continuous efforts in providing
me with necessary knowledge and talents during my undergraduate and graduate
education.
My special thanks are given to Prof. Dr. Greg Neimeyer, my American mentor, who
supervised me as a visiting research scholar in University of Florida at Department of
Psychology. He has worked warmly and closely with me from our first meeting. I
would also like to express my thanks to Assist. Prof. Dr. Gizem Aksoy Toska,
Jennifer M. Taylor and Assist. Prof. Dr. Ryan Duffy who assisted and worked
intimately with me.
x
I would like to express my appreciation to Bilge Uzun Özer, Evrim Çetinkaya Yıldız,
Asiye Parlak Rakap, Esma Hacıeminoğlu, Nurdane Aydemir, and Reyhan Zengin for
their support and help during this study.
I would like to express my sincere gratitude and love to my husband Musa who
patiently shared my stresses during this study. His patience, encouragement,
compassion, and flexibility have been exceptional. His confidence in my success has
been nurtured and sustained me throughtout my studies.
No words can fully express my gratitude to my parents, my sister and my brother
who have always trusted, encouraged and listened to me patiently in my life.
Especially I would like to thank to my sister, Hilal, for her assistance for editing.
My son and my daughter, thank you for sharing your mummy, I hope I will have
much time for playing with you.
I also express my thanks to students who voluntarily participated in this study.
This study was supported by the State Planning Organization (DPT) Grant No: BAP-
08-11-DPT-2002K120510
xi
TABLE OF CONTENTS
PLAGIARISM ............................................................................................................ iii
ABSTRACT ................................................................................................................ iv
ÖZ ............................................................................................................................... vi
DEDICATION .......................................................................................................... viii
ACKNOWLEDGMENTS .......................................................................................... ix
TABLE OF CONTENTS ............................................................................................ xi
LIST OF TABLES .................................................................................................... xiv
LIST OF FIGURES ................................................................................................... xv
CHAPTERS
1. INTRODUCTION ................................................................................................... 1
1.1 Background to the Study ................................................................................... 1
1.2 Purpose of the Study ......................................................................................... 6
1.3 Proposed Path Model and Hypotheses .............................................................. 7
1.4 Significance of the Study ................................................................................ 13
1.5 Definition of Terms ......................................................................................... 18
2. REVIEW OF THE LITERATURE ........................................................................ 20
2.1 Theories and Models of Career Choice and Development ............................. 20
2.1.1 Established Theories of Career Choice and Development ................... 21
2.1.2 Emerging Theories of Career Choice and Development ..................... 30
2.2 Theoretical Framework of the Study: Social Cognitive Career Theory
(SCCT)..............................................................................................................34
2.3 Demographic Variables and Career Indecision............................................... 47
2.4 Factors Contributing to Career Indecision ...................................................... 49
2.5 Research on Proposed Model Variables ......................................................... 50
2.5.1 Locus of Control and Career Indecision .............................................. 51
2.5.2 Parental Influence on Career Indecision .............................................. 53
xii
2.5.3 Career Decision Making Self-Efficacy and Career Indecision ............ 58
2.5.4 Career Outcome Expectations and Career Indecision .......................... 60
2.6 Studies on Career Indecision in Turkey .......................................................... 62
2.7 Summary ......................................................................................................... 66
3. METHOD ............................................................................................................... 68
3.1 Sampling Procedure and Participants.............................................................. 68
3.2 Data Collection Instruments ............................................................................ 69
3.2.1 Demographic Information Form .......................................................... 70
3.2.2 Career Decision Scale (CDS) ............................................................... 70
3.2.3 Career Decision Self-Efficacy Scale- Short Form (CDSE-SF)............ 73
3.2.4 Career Outcome Expectations and Exploratory Intentions Scale
(OEX-EI)……………………………………………………………..74
3.2.5 Translation Procedure of the CDS, CDSE-SF, and OEX-EI ............... 76
3.2.6 Validity and Reliability of the Turkish Version of CDS ..................... 79
3.2.7 Validity and Reliability of the Turkish Version of CDSE-SF ............. 84
3.2.8 Validity and Reliability of the Turkish Version of OEX-EI ................ 90
3.2.9 Parental Attitude Scale (PAS) .............................................................. 94
3.2.10 Rotter‟s Internal External Locus of Control Scale (IELOC) ............... 96
3.3 Procedure......................................................................................................... 97
3.4 Data Analyses.................................................................................................. 97
3.4.1 Path Analysis ........................................................................................ 98
3.5 Limitations of the Study ................................................................................ 102
4. RESULTS ............................................................................................................ 104
4.1 Preliminary Analyses .................................................................................... 104
4.1.1 Missing Data and Outlier Analyses ................................................... 104
4.1.2 Assumptions of the Path Analysis ..................................................... 105
4.2 Demographic Analyses ................................................................................. 110
4.3 Descriptive Statistics and Correlations ......................................................... 111
xiii
4.4 Path Analysis: Testing the Proposed Career Indecision Model .................... 117
4.5 Path Analysis: Testing the Trimmed Career Indecision Model .................... 122
4.5.1 Direct and Indirect Relationships ....................................................... 126
4.5.2 Hypotheses Testing ............................................................................ 128
5. DISCUSSION ...................................................................................................... 132
5.1 General Discussion........................................................................................ 132
5.2 Hypothesized Relationships between Locus of Control and Career
Indecision ........................................................................................................ 134
5.3 Hypothesized Relationships between Perceived Parental Attitudes
and Career Indecision ..................................................................................... 136
5.4 Hypothesized Relationships between Career Decision-Making
Self-Efficacy and Career Indecision ............................................................... 139
5.5 Hypothesized Relationships between Career Outcome Expectations
and Career Indecision ..................................................................................... 140
5.6 Implications and Recommendations for Research and Practice ................... 141
REFERENCES ......................................................................................................... 146
APPENDICES ......................................................................................................... 179
A. DEMOGRAPHIC INFORMATION FORM ................................................... 180
B. SAMPLE ITEMS OF CAREER DECISION SCALE ..................................... 181
C. SAMPLE ITEMS OF CAREER DECISION SELF-EFFICACY
SCALE SHORT-FORM……….……………...………………………………182
D. SAMPLE ITEMS OF CAREER OUTCOME EXPECTATIONS
SCALE .............................................................................................................. 183
E. SAMPLE ITEMS OF PARENTAL ATTITUDES SCALE ............................. 184
F. SAMPLE ITEMS OF ROTTER‟S INTERNAL EXTERNAL LOCUS
OF CONTROL SCALE ..................................................................................... 185
G. TURKISH SUMMARY ................................................................................... 186
H. CURRICULUM VITAE .................................................................................. 211
xiv
LIST OF TABLES
TABLES
Table 3.1 Factor Loadings of Indecision Subcale Items………………………….82
Table 3.2 Factor Loadings of CDSE-SF Items…………………………………...89
Table 3.3 Factor Loadings of OEX-EI Scales…………………………………....93
Table 4.1 Indices of Normality for Study Variables……………………………107
Table 4.2 Means, Standard Deviations and Intercorrelations…………………..114
Table 4.3 Acceptable Cutoff Values for Goodness of Fit Indices……………...118
Table 4.4 Summary of Model Fit Statistics for the Proposed Model………......119
Table 4.5 Summary of Model Fit Statistics for the Trimmed Model………......123
Table 4.6 Standardized Total, Direct, and Indirect Estimates of the Trimmed
Model…………………………………………………………….......127
xv
LIST OF FIGURES
FIGURES
Figure 1.1 Current study in the context of the Lent et al (1994) Model…………10
Figure 1.2 Proposed model of Career Indecision……………….…....………….11
Figure 2.1 Model of Person, contextual, and experiential factors affecting
career-related choice behavior………………..……………………....43
Figure 3.1 Translation and Pilot studies of CDS, CDSE-SF,
and OEX-EI………………………………………...…………………78
Figure 3.2 Scree Plot of Indecision Subcale……………………...……………...81
Figure 3.3 Scree Plot of Career Decision Self-Efficacy Scale
Short-Form…………………………………………………...…….….88
Figure 3.4 Scree Plot of Outcome Expectations and Exploratory
Intentions Scale…………………………………………………......…92
Figure 4.1 Scatterplot Matrix of all Study Variables…………………………...108
Figure 4.2 Scatterplot of Standardized Predicted Values by Standardized
Residuals………………………………………………………...........109
Figure 4.3 Standardized Path Coefficients for the Proposed Model…….……. .121
Figure 4.4 Standardized Path Coefficients for the Trimmed Model…….……...125
1
CHAPTER I
INTRODUCTION
Alice: Would you tell me, please, which way I ought to walk from here?
The cat: That depends a good deal on where you want to get to
Alice: I don't much care where...
The cat: Then it doesn't matter which way you walk!
...
Lewis Carroll, Alice in Wonderland.
1.1 Background to the Study
Career decision making is one of the significant and inevitable tasks of life. In this
regard, university years, when students have to make decisions regarding
employment and further education are crucial with respect to career decision-making
process. However, for many young people, making a career decision can be a
difficult and confusing task (Gati, Krausz, & Osipow, 1996) that has lifelong
consequences for the individual's vocational future, psychological and physical well-
being, social acceptance, hence, overall quality of life (Mann, Harmoni, & Power,
1989). Accordingly, career indecision is one of the common presenting problems for
students seeking counseling at most university counseling centers (Kelly & Pulver,
2003; Taylor, 1982). Specifically, from twenty to sixty percent of university students
were found to experience career indecision (e.g., Gordon, 1995).
2
Career indecision has been viewed as one of the vital and central topics of career
psychology, which has captured the attention of many researchers due to its financial
and psychological costs (Betz, 1992; Osipow, 1999). The term career indecision has
been widely used with reference to problems related to career development,
particularly problems in making career-related decisions. Career indecision is viewed
as a developmental problem within the career maturation process “that results from a
lack of information about self or the world of work” (Chartrand, Martin, Robbins, &
McAuliffe, 1994, p. 55). Hawkins-Breaux (2004) makes the general definition of the
construct as “point in the career development process when individual must take
action on a course or direction for the future, and for any number of reasons, he or
she cannot move forward in the process” (p. 20). Additionally, career indecision
status refers to “an inability to select a career goal or having selected a career goal, to
experience significant feelings of uncertainty about the goal” (Callahan &
Greenhaus, 1990, p. 80). Consequently, career indecision is viewed as a severe
problem characterized by the experience of high level of uncertainty regarding one‟s
career choices (Lopez & Ann-Yi, 2006).
A considerable body of literature has focused on factors that play important role on
career indecision. Studies on career indecision have mainly focused on personality
characteristics as possible distinguishing factors of decided and undecided students
regarding their career. Accordingly, career indecision has been measured in relation
to various personality constructs including locus of control (Fuqua & Hartman, 1983;
Taylor, 1982), anxiety (Newman, Fuqua, & Minger, 1990), self-efficacy (Betz &
3
Klein-Voyten, 1997; Taylor & Betz, 1983), vocational maturity (Fuqua, Blum, &
Hartman, 1988), irrational beliefs, fear of success, (Taylor, 1982), self-esteem
(Creed, Patton, & Bartrum, 2004), identity formation (Tokar, Withrow, Hall, &
Moradi, 2003), perfectionism, fear of commitment (Leong & Chervinko, 1996), and
pessimism (Saka & Gati, 2007). Most of the findings support the notion that, the
undecided students seem to be more anxious, dependent, externally controlled, have
lower self-efficacy than the decided students.
In addition to personality characteristics, many theorists (e.g., Bratcher, 1982; Roe,
1957) and researchers (e.g., Blustein, Walbridge, Friedlander, & Palladino, 1991;
Lopez & Andrews, 1987) emphasized the role of familial factors on career decisions
of individuals. In a sample of young adults, for example, O‟Neil et al., (1980)
reported that fifty percent of young adults felt their family had fairly or extensively
influenced their career decision-making. According to Bratcher (1982), families
establish certain patterns and principles to provide a sense of homeostasis within the
family. Thus, these patterns influence behavior, including career decision-making
behavior. Similarly, Lopez and Andrews (1987) conceptualized young adults‟ career
indecision as the outcome of a larger set of transactions between person and family.
Likewise, Büyükgöze Kavas (2005) and IĢık (2007) found that family interaction
was the most influential factor of the university students‟ career decision. Whiston
and Keller (2004), a result of their review of both qualitative and quantitative studies
investigated the influences of family variables on career development, concluded that
4
the career decision-making of college students and young adults were influenced by
parental emotional support, autonomy support, encouragement, and warmth.
Research on career indecision indicates that variables such as gender and age are
frequently investigated demographic characteristics. Regarding gender, previous
studies have generally reported no difference on career indecision (e.g., Kang, 2009;
Osipow, Carney, & Barak, 1976). On the other hand, majority of the investigations
suggest a negative relationship between age and career indecision (e.g., Peng & Herr,
2002).
To date, various theories of career choice and development such as trait-oriented
theories, developmental theories, social learning and cognitive theories, person-in-
environment theories and constructivist theories have been developed to understand
and explore career decision-making process of individuals (Zunker, 2006). Although
most of these theories have usually been reflected Eurocentric values such as
individualism and self-actualization (Weiss, 2000), the significant increase in the
minority population in the USA and the intense cross-cultural interaction have led to
reexamination of the several theories (e.g., Holland‟s career typology, Super‟s life-
span/ life-space theory) for different cultural groups. In the recent years researchers
underlined the several interacting factors and contextual issues constitute significant
part of career decision-making process (Zunker, 2006). Accordingly, one of the
contemporary approaches, Social Cognitive Career Theory (SCCT; Lent, Brown &
Hackett, 1994, 2000) has become a frequently used and popular framework for
5
studying academic and career development, due to its comprehensive structure which
provides a framework for assessing a wide range of personal, familial, cultural, and
environmental factors that can account for one‟s career choice and development.
Social Cognitive Career Theory attempts to build conceptual linkages with existing
career development theories (Lent et al., 1994). It has primarily derived from
Bandura‟s (1986) general social cognitive theory that emphasizes the interactions
between person, contextual, and learning factors in shaping career choice behaviors
(Lent & Brown, 1996; Lent et al., 1994). To conceptualize the complex interacting
influences among persons, their behavior, and their environments, SCCT adopts
Bandura's (1986) triadic reciprocal model of causality. The triadic model holds that
person attributes (such as internal cognitive and affective states), external
environmental factors, and overt behavior each operates as interactive sets of
variables that mutually influence one another. In conceptualizing personal
determinants of career development, SCCT highlights three linked variables through
which individuals help regulate their own career behavior: self-efficacy beliefs,
outcome expectations, and personal goals (Lent & Brown, 1996). Thus, it can be said
that the model emphasized three social cognitive mechanisms: (a) self-efficacy, (b)
outcome expectations, and (c) personal goals that form the core of a social cognitive
career approach to vocational behavior.
As highlighted in the model, cultural and contextual variables play a vital role in
career decision-making process (Lent, Brown, & Hackett, 2000). Because the theory
6
directly considers the race and ethnicity variables as personal inputs, there are several
studies conducted with different cultural groups such as African Americans, Asian
Americans, Italians, and Chinese (e.g., Constantine, Wallace, & Kindaichi, 2005; Jin,
Watkins, & Yuen, 2009; Lent, Brown, Nota, & Soresi, 2003) to test the SCCT
model. Although SCCT has received considerable research attention since its
introduction, there is a need for further cross-cultural and cross-national studies on
SCCT to test the cultural validity of the model (Lent et al., 2003). Thus, the aim of
the present study was to test the proposed path model of career indecision, utilizing
SCCT as a framework, among Turkish university students.
1.2 Purpose of the Study
The aim of the current study was to test a model of career indecision based on Social
Cognitive Career Theory (Lent et al., 1994) to understand the factors that contribute
to career indecision among Turkish university students. As stated by Lent et al.,
(1994), “although tests of the full models of interest, choice, and performance may
not be practical in a single study, focused tests of particular hypotheses or sets of
hypotheses may add cumulatively to the theory‟s empirical base” (p. 115). Thus, in
the present study the proposed path model (Figure 1.2) was designed to investigate
the role of locus of control, perceived parental attitudes (acceptance/ involvement,
strictness/ supervision, psychological autonomy), career decision-making self-
efficacy, and career decision-making outcome expectations in predicting career
7
indecision among university students. More specifically the present study addressed
the following research question:
“To what extent the career indecision is explained by the proposed path model that
consisted of locus of control, perceived parental attitudes (acceptance/ involvement,
strictness/ supervision, psychological autonomy), career decision-making self-
efficacy and career decision-making outcome expectations?”
1.3 Proposed Path Model and Hypotheses
Lent et al. (1994) suggested the partial testing of the models of interest, choice, and
performance rather than the full model testing. Accordingly, personality, background
context, self-efficacy and outcome expectations factors, which comprised the core of
the career choice model of SCCT, were included in the current proposed model of
career indecision. Thus, locus of control was selected as the personality variable
because it was viewed as a reliable and central variable in the career decision process
(Luzzo & Ward, 1995). Because individuals mostly seek assistance from family
members with regard to their career decisions (Whiston & Keller, 2004), it is
important to understand and determine the influences of family, specifically parents
on career decision process that's why parental attitudes were included to the model.
In the present study, self-efficacy and outcome expectations were selected as
mediator variables, because they were identified as major mediators of SCCT (Lent
et al., 1994).
8
In the proposed path model, locus of control, perceived parental attitudes
(acceptance/ involvement, strictness/ supervision, psychological autonomy) career
decision-making self-efficacy and career decision making outcome expectations
were independent variables and career indecision was the dependent or outcome
variable of this study. More specifically, career decision-making self-efficacy and
career decision making outcome expectations were tested as mediators between locus
of control, perceived parental attitudes and career indecision in this proposed path
model. Thus, the relation between locus of control and career indecision will be
substantially strengthened when career decision-making self-efficacy is included as a
mediator. The relation between locus of control and career indecision will be
substantially strengthened when career decision-making outcome expectations is
included as a mediator.
However, there are few differences observed between the current study that proposed
path model of career indecision in the context of SCCT and the Lent and his
colleagues‟ (1994) model. First, there are many personal inputs which were
described by Lent et al. (1994) such as age, gender, and race, however, only locus of
control as a personality variable was included in the current study. Second, the
variables related to context, only the individual background context of family
variables was included in the proposed path model. Third, learning experiences
which are viewed as mediators of the relation between personal inputs and self-
efficacy and between background context and self-efficacy were not assessed in the
present study. Forth, outcome expectations were assessed and included in the
9
proposed path model which is predicted by self-efficacy directly. Finally, in the
current model, although interests were not considered, three emphasized social
cognitive mechanisms of the Social Cognitive Career Model which are self-efficacy
beliefs, outcome expectations and goal representations (Lent et al., 1994) were
examined (Figure 1.1). Variables symbolized by black boxes were not assessed in the
current proposed path model. The relationships offered by Lent et al. (1994) are
demonstrated as dotted arrows.
10
Variables in the present model
Variables not included
Path in the present model
Path offered by Lent et al. (1994)
Figure 1.1 Current Study in the Context of the Lent et al. (1994) Model
Personality
Goals
Background
Context
Outcome
Expectations
Self-efficacy
11
Psy
cholo
gic
al
Au
ton
om
y
Variable
Locu
s of
Con
trol
Acc
epta
nce/
Involv
emen
t
Str
ictn
ess/
Su
per
vis
ion
C
are
er
Ou
tcom
e
Exp
ecta
tion
s
Care
er
Deci
sion
-mak
ing
Sel
f-ef
fica
cy
Care
er
Ind
ecis
ion
Ind
epen
den
t V
ari
ab
les
M
edia
tor
Va
riab
les
D
epen
den
t V
ari
ab
le
Fig
ure
1.2
Pro
pose
d M
odel
of
Car
eer
Ind
ecis
ion
1
3
10
2
4 A
7 A
9
6 A
5 A
11
12
8
12
The following hypotheses will be tested in the present study:
Hypothesis 1: There will be a relation between locus of control and career indecision.
(Path 1)
Hypothesis 2: Locus of control will be related to career indecision indirectly
(a) through career decision-making self-efficacy (Path 2 and Path 11)
(b) through career decision-making outcome expectations (Path 3 and Path 12)
Hypothesis 3: Perceived parental acceptance/ involvement will be related to career
indecision indirectly
(a) through career decision-making self-efficacy (Path 4 and Path 11)
(b) through career decision-making outcome expectations (Path 5 and Path 12)
Hypothesis 4: Perceived parental strictness/ supervision will be related to career
indecision indirectly
(a) through career decision-making self-efficacy (Path 6 and Path 11)
(b) through career decision-making outcome expectations (Path 7 and Path 12)
Hypothesis 5: Perceived parental psychological autonomy will be related to career
indecision indirectly
(a) through career decision-making self-efficacy (Path 8 and Path 11)
(b) through career decision-making outcome expectations (Path 9 and Path 12)
13
Hypothesis 6: There will be a relation between career decision-making self-efficacy
and career indecision. (Path 11)
Hypothesis 7: Career decision-making self-efficacy will be related to career
indecision indirectly through career decision-making outcome expectations. (Path 10
and Path 12)
Hypothesis 8: There will be a relation between career decision-making outcome
expectations and career indecision. (Path 12)
1.4 Significance of the Study
As emphasized by many theorists (e.g., Erikson, 1968; Super, 1980), high school
years and years after high school are conceptualized as the time period when students
gather information about themselves and the world of work through a process of
exploration (Patton & Lokan, 2001). According to Super (1980), exploration stage
takes place between the ages 14 to 25.
In Turkey, due to the structure of the education system career exploration stage
seems to be experienced differently by the adolescents. According to the current
system, students have to make their decisions regarding their career during high
school years. This system required decision making process could be regarded as
having two stages. First stage is choosing a field (Turkish Languages-Mathematics,
14
Sciences, Social Sciences, and Foreign Languages) on the 10th
grade that would
determine the range of possible programs that they could study at university. Second
is the entering nationwide university entrance exam. Students were selected and
placed in undergraduate programs based on that exam scores. However, the
discrepancy existing between the number of potential degree candidates and the
actual number of student placements in academic programs is enormous. Each year
only about one-third of the candidates placed in a university program, leaving two-
thirds without higher education (Mızıkacı, 2006). Therefore, in order to enter one of
the highly ranked universities, students and parents extremely focus on being
successful in the exam. Throughout the preparation process for the entrance exam
many students and parents seem to ignore the importance of career exploration and
may not consider engaging career exploration activities. However, when students
enter a university it becomes difficult to change the department. Universities provide
very limited and competitive options for undecided students. In some universities in
Turkey, one option for undecided students could be undergraduate minor programs
(which allow academically successful students to become knowledgeable in another
subject area that they are interested in) and the other one could be double major
programs (which allow academically successful students to work towards a second
undergraduate diploma in another department). As the current higher education
system do not offer much opportunities to undecided students to change their
program or department, a considerable number of students who are placed into
academic programs after passing the exam, re-take the entrance exam several times
to enter the academic program that they desire. For example, in 2010, 23% of the
15
students who entered university entrance exam were retaking the exam even they
were currently university students (ÖSYM, 2010). Thus, it is possible to claim that,
university entrance exam achievement may not be enough for some students to fulfill
their career decisions and be satisfied with the choice.
In the current university placement system, it is not clear to what extent university
students are left with the consequences of possible early, immature and undesirable
choices. In this regard at university level, it is particularly important to assess factors
that contribute to career indecision and relevant skills that are essential to facilitate
students‟ career planning. Otherwise, as a long-lasting consequence of career
indecision many students may be at risk for being unsatisfied with the occupation
they eventually obtain.
Many career development theories have developed models to investigate the factors
that have impact on career indecision. However, most of these models have been
developed in Euro-American cultures reflecting an individualistic orientation. Thus,
these theories may not be applicable for ethnic minorities and culturally diverse
populations that served collectivistic notion (Weiss, 2000). However, Social
Cognitive Career Theory (SCCT) which involves an examination of the personal and
contextual factors that may affect the career development process may provide a
useful framework for understanding the issues and obstacles characterizing the career
development of women and members of particular racial or ethnic minority groups
(Lent et al., 1994). SCCT was preferred as the theoretical framework of the current
16
study because SCCT emphasizes several cognitive-person variables (e.g., self-
efficacy, outcome expectations, and goals), and on how these variables interact with
other aspects of the person and his or her environment (e.g., gender, ethnicity, social
supports, and barriers) to help shape the course of career development (Lent et al.,
2000).
While western cultures emphasize the significance of making personal decisions,
choice, concluding judgments, and defending personal opinions, eastern cultures
stress the importance of collective or group decisions, thoughts of significant others
in decision-making process (Mau, 2001). Turkish culture, which is close to
collectivistic orientation, family and social environment seem to have significant
influences on life decisions (Mocan-Aydın, 2000). Thus, contextual factors such as
family are expected to be related to career decisions might be essential to investigate.
The present study through taking SCCT as a theoretical framework, aims to
investigate the relationship between career indecision and locus of control, parental
attitudes (acceptance/ involvement, psychological autonomy, strictness/ supervision),
career decision-making self-efficacy, and career decision-making outcome
expectations.
It can be stated that no published research in Turkey has examined the combined
influence of aforementioned model and related variables on career indecision. In this
respect, this study aimed to address gaps in career indecision research with an
uninvestigated population. Furthermore, one of the aims of this study is to make
17
translation, validity, and reliability studies of three scales; Career Decision Scale
(CDS; Osipow, Carney, Winer, Yanico, & Koschier, 1976), Career Decision Self-
Efficacy Scale-Short Form (Betz & Klein, 1996), and Career Outcome Expectations
Scale (Betz & Klein-Voyten, 1997).
As stated by Saka and Gati (2007), assessing and identifying the sources of
individuals' career decision-making difficulties is the first step before assisting these
individuals. Career related problems mostly career indecision may lead to serious
psychiatric syndromes or vocational issues if ignored or ineffectively addressed in
counseling (Hinkelman & Luzzo, 2007). For example, significant positive
relationship between depression and career indecision was reported among university
students (Saunders, Peterson, Sampson, & Reardon, 2000). Thus, university
counseling centers, university career planning centers as well as academic
departments need to develop more comprehensive understanding about underlying
factors of career indecision among students. Therefore, it is also hoped that the
findings of the present research may provide further insight to practitioners working
in university counseling centers and university career planning centers when
measuring career indecision, planning preventive and remedial programs and
interventions for clients with career indecision and related issues university students.
18
1.5 Definition of Terms
Locus of control refers to “a person‟s expectancies with regard to whether
reinforcement is controlled internally (i.e., by oneself) or externally (i.e., by fate,
chance, luck, or powerful others)” (Jolley & Spielberger, 1973, p. 443).
Parental Attitudes are conceptualized as three different patterns those are acceptance/
involvement, strictness/ supervision, and psychological autonomy. Acceptance/
involvement refers to the degree to which individuals perceive their parents as
loving, responsive, and involved; strictness/ supervision reflects ultimate parental
monitoring and supervision of the children; and psychological autonomy refers to
noncoerceive and democratic discipline of parents (Lamborn, Mounts, Steinberg, &
Dornbush, 1991).
Career Indecision is the state of having difficulties in setting a career goal, in
particular, either the inability or unwillingness to choose a career goal, or having the
feeling of uncertainty toward an expressed career goal (Callahan & Greenhaus,
1992). According to Osipow (1999), indecision refers to “a temporary state or
developmental phase through which individuals may pass on their way to reaching a
decision” (p. 147). Guay, Senécal, Gauthier, and Fernet (2003) defined career
indecision “as an inability to make a decision about the vocation one wishes to
pursue” (p. 165).
19
Career Decision-making Self-efficacy is individual‟s belief that he or she can
successfully complete tasks necessary to make career decision (Taylor & Betz,
1983). In addition, it refers to beliefs in competencies with respect to the behaviors
necessary in particular career-relevant domain (Betz & Klein-Voyten, 1997).
Outcome Expectations “involve beliefs in the consequences of performing given
behaviors” (Betz, & Klein-Voyten, 1997, p. 181). According to Bandura (1977),
outcome expectancy is defined as a person‟s estimate that a given behavior will lead
to certain outcomes (p. 193).
Career Decision-Making Outcome Expectancies refers to “beliefs regarding the long
term consequences of success in specific educational or career decision-making
behaviors. Similarly, outcome expectations regarding career decision-making
behaviors were defined as “the belief that those behaviors would be useful to
subsequent career options and decisions” (Betz, & Klein-Voyten, 1997, p. 182).
20
CHAPTER II
REVIEW OF THE LITERATURE
This chapter presents the review of the related literature starting with a summary of
major theories and models of career choice and development. Then, comprehensive
information regarding theoretical framework of the study which is the Social
Cognitive Career Theory (Lent et al., 1994) was provided. The chapter continues
with the major research findings concerning the demographic variables, proposed
model variables and career indecision. Lastly, the chapter mentions the studies on
career indecision in Turkey.
2.1 Theories and Models of Career Choice and Development
In general “a theory is a series of connected hypothetical statements designed to
explain a particular behavior or set of behaviors” (Swanson & Fouad, 1999, p. 3). As
stated by Brown (2003), “theories provide us with simplified pictures or road maps
to the career development process” (p. 22). To date, several career theories have been
designed to explain career development and career decision making (Osipow, 1990).
In the following section, brief descriptions of mostly cited established and emerging
theories of career choice and development as Parsons‟ Trait and Factor Theory,
Theory of Work Adjustment, Holland‟s Career Typology, Super‟s life-span/ life-
21
space theory, Gottfredson‟s Theory of Circumscription and Compromise,
Krumboltz‟s Learning Theory of Career Counseling, Cognitive Information
Processing Approach, Social Cognitive Career Theory, Brown‟s Values-Based
Holistic Model of Career and Life-Role Choices and Satisfaction, Ecological Model
of Career Development, and Career Construction Theory will be provided
(Amundson, Harris-Bowlsbey, & Niles, 2009; Brown, 2003; Gysbers, Heppner, &
Johnston, 2002; Luzzo, 2000; Niles & Harris-Bowlsbey, 2005; Sharf, 2006; Walsh &
Osipow, 1990; Zunker, 2006).
2.1.1 Established Theories of Career Choice and Development
Trait-and-factor theory (TFT) is the first conceptual framework proposed by Parsons
(1909) to understand and explain career decision-making process. The term trait
refers to a characteristic of an individual that can be measured through testing and
factor refers to a characteristic required for successful job performance. Thus, the
terms trait and factor refer to the assessment of characteristics of the person and the
job (Sharf, 2006). Parsons‟ approach consisted of three steps used to help someone
make an occupational choice (Amundson et al., 2009).
In the wise choice of a vocation there are three broad factors: (1) a clear
understanding of yourself, aptitudes, abilities, interests, resources, limitations,
and other qualities; (2) advantages and disadvantages, compensation,
opportunities, and prospects in different lines of work; (3), true reasoning on
the relations of these two groups of facts (Parsons, 1909, p. 5).
22
Thus, the theory mainly based on the process of matching individuals‟ traits with
requirements of occupations. Accordingly, the major goal of career counseling is
integrating information about one‟s self and about occupations (Sharf, 2006). Niles
and Harris-Bowlsbey (2005) listed the basic assumptions of the theory as
occupational choice is a single and point-in-time event, career development is mainly
a cognitive process based on rational decision-making, occupational adjustment rely
on the degree of concurrence between characteristics of worker and work demands,
due to one‟s self-characteristics, each worker is best fitted for a specific type of
work, and groups of workers in different occupations have different self-
characteristics. The development of standardized assessment instruments,
occupational analysis procedures and the importance of individual values have been
emphasized by the trait and factor theory viewed useful in career counseling (Zunker,
2006). The theory was criticized because it viewed career decisions are based
primarily on measured traits that limits the inclusion of many other possible factors
that can be considered in the career development and career decision making process.
Even if the approach emphasizes identifying the individual traits and factors, it does
not provide any explanations regarding how interests, values, aptitudes, achievement
and personality grow and change (Herr, Cramer, & Niles, 2004). Further, limitations
include insufficient attention to sex, race, and socioeconomic status (Betz, Fitzgerald,
& Hill, 1989). There is little research supporting or refuting the theory (Sharf, 2006).
The theory of work adjustment (TWA) grew out of the University of Minnesota‟s
Work Adjustment Project to study job satisfaction and worker adjustment (Dawis,
23
2005; Dawis & Lofquits, 1984). Since early 1990s it is referred to as the person
environment correspondence (PEC) counseling (Lofquist & Dawis, 1991; Osipow &
Fitzgerald, 1996). TWA has two assumptions: people have two types of needs as
biological (e.g., need for food) and psychological (e.g., social acceptance). Second
assumption is that work environments have requirements parallel to the needs of
individuals. When the needs of individuals in an environment (work) and those of the
environment are satisfied, correspondence exists (Brown, 2003). The theory based on
the idea that “most problems brought to counselors by clients stem from lack of fit,
or discorrespondences between person and the environment” (Lofquist & Dawis,
1991, p. 1). In order to survive, the individual and the work environment must
achieve some degree of correspondence. The effort of the individual to maintain this
correspondence is called work adjustment (Osipow & Fitzgerald, 1996). According
to the approach, work includes human interaction and sources of satisfaction,
dissatisfaction, rewards, stress and many other psychological variables. Thus, to
understand work adjustment, the personality characteristics of the worker such as
abilities and psychological needs and the structure of the target environment must be
known. In addition, the theory emphasized the importance of the relationship
between job satisfaction and work adjustment because job satisfaction is viewed as a
significant indicator of work adjustment (Dawis, 2005). The position that individual
needs and values are significant components of job satisfaction is an important
contribution to the study of career development (Zunker, 2008). The theory is subject
to some criticisms like it does not directly address boundaries of the effects of
24
correspondence. In addition, the distinction between the actual and perceived person
and environment received little research attention (Edwards, 2008).
Holland’s career typology viewed personality as a result of the interaction of
inherited characteristics, the type of environment the parents provide, individual
reinforcement experiences, the activities to which the individual is exposed, and the
interests and competencies that grow out of the activities (Holland, 1997; Osipow,
1990). According to Holland (1985), his approach can be described as structural and
interactive because it organizes information about people and occupations and
supposes that interaction of people and environments lead to vocational and social
behavior. Career choice can be seen as an expression of personality into the world of
work. A comparison of self with the perception of an occupation and following
acceptance or rejection is a major determinant in career choice. Holland proposes six
different personality types which are realistic, investigative, artistic, social,
enterprising, and conventional. According to Holland, a person can be typed into one
of these categories by expressed or displayed vocational or educational interests, by
employment, or by scores obtained on several instruments such as the Self-Directed
Search. Parallel to these personality types, six work environments as realistic,
investigative, artistic, social, enterprising, and conventional were offered (Holland,
1985). Accordingly, the theory proposes four basic assumptions. Firstly, people can
be classified as one of these six personality types. Secondly, environments can be
also categorized as one of six types. Thirdly, people seek environments which allow
them to use their skills and abilities, express their attitudes and values, and take on
25
problems and roles that fit them. Lastly, the interaction between personality and
environment determines individual behavior (Hartung & Niles, 2000). Holland
graphically represented six personality style and environments around a hexagon to
show relationships within and between types of personality and environments. As a
result, three important constructs arise as consistency, differentiation, and identity
(Niles & Harris-Bowlsbey, 2005). Consistency refers that the shorter the distance on
the hexagon between any two types or environments, the more similar are those
types or environments (Hartung & Niles, 2000; Niles & Harris-Bowlsbey, 2005).
Differentiation refers to the degree of crystallization of among types. Identity refers
to the clarity and stability of a person‟s goals (Sharf, 2006). Consequently, a
congruent person-environment match most likely results in a more stable vocational
choice, greater satisfaction, greater vocational achievement, and better maintenance
of personal stability (Brown, 2003; Zunker, 2006). Holland‟s theory has investigated
more than other career development theories. However, it criticized because the
theory does not consider geographical location, non-Holland personality factors,
education, and personal responsibilities to family (Sharf, 2006).
Super’s life-span/ life-space theory is mainly interested in determining how self-
concept is implemented in vocational behavior (Zunker, 2006). Super (1990)
described the theory as “a synthesis of developmental, differential, social and
phenomenological psychology” (p. 194). In addition, career development is viewed
as a lifelong process (Hartung & Niles, 2000). Self-concept, life-span and life space
are three important segments of the theory (Gysberg et al., 2002). Self-concept can
26
be defined as internalized personal view of self and individual‟s view of the situation
or condition in which he or she exists (Brown, 2003). The life span consists of five
chronological developmental stages of life from birth to death like growth (birth to
age 14 / 15), exploration (ages 15-24), establishment (ages 25-44), maintenance (45-
65), and decline (ages 65+). These stages are characterized by a set of vocational
developmental tasks. An individual‟s progress in achieving the tasks through the
stages described as vocational or career maturity. Life space refers to the particular
roles that a person plays at any time in the life span (Hartung & Niles, 2000; Osipow,
1990). Goals of the theory can be summarized as enhancing the level of career
maturity, strengthening self-concept, as well as identifying interests, abilities, and
values and distributing them across life roles (Amundson et al., 2009). Life–span,
life-space theory constructs on fourteen propositions. Accordingly, the first three
propositions point out that people have different abilities, interest, and values hence;
they may be qualified more than one occupation. There are many occupations
accessible for an individual so that no person fits only one occupation. The next six
propositions emphasize on the self-concept and its implementation in career choice,
and on the concepts of career patterns and career maturity. The next five propositions
are related to the synthesis and compromise between individual and social factors
and work and life satisfactions. The last one stresses work and occupation as the
focus for personality organization as well as the interplay of such life roles as
worker, student, homemaker, and citizen (Gysberg et al., 2002). Super (1990)
presented a life-stage model by means of a life rainbow. This two-dimensional
graphic is a representation of longitudinal dimension of life span corresponding
27
major life stages and the second dimension is named as life space refers to the roles
played by individuals as they progress through developmental stages. Further, he
developed an archway model to show the changing diversity of life roles over the life
span. Further, the model stressed how career development process affected by
biological, psychological and socioeconomic factors (Zunker, 2006). Contributions
of Super‟s theory acknowledged by many authors (e.g., Hackett, Lent, & Greenhaus,
1991; Osipow & Fiztgerald, 1996). According to Salomone (1996), however, Super
has not stated testable hypotheses for various propositions of his theory. Also the
relationship between theoretical propositions and empirical findings is not clearly
explained (Salomone, 1996).
Gottfredson’s Theory of Circumscription and Compromise is a developmental theory
of occupational aspirations which helps to explain how people see themselves with
respect to society and individuality (their values, feeling, and interests).
Circumscription is described as a process in which young people eliminate
unacceptable occupational alternatives. Gottfredson (1981) proposes four stages of
circumscription that are orientation to size and power (ages 3-5), orientation to sex
roles (ages 6-8), orientation to social valuation (ages 9-13), and orientation to the
internal unique self (ages 14 and older). Also, compromise is described as a process
in which young people give up alternative that they may like for ones that may be
more accessible to them (Niles & Harris-Bowlsbey, 2005; Sharf, 2006). The theory
based on four basic assumptions:
28
(1) The career development process begins in childhood; (2) career
aspirations are attempts to implement one‟s self-concept; (3) career
satisfaction is dependent on the degree to which the career is congruent
with self-perceptions; and (4) people develop occupational stereotypes
that guide them in the selection process (Brown, 2003, p. 40).
According to Gottfredson (2005), self-concept consisted of both social and
psychological self. The social self includes self-perceptions about intelligence, social
status, and gender, whereas the psychological self is composed of variables as values
and personality variables. People develop cognitive maps of occupations that are
organized along with masculinity/ femininity of the occupation, the prestige of the
occupation, and fields of work. Of these dimensions, the sex-type assigned to the
occupation and the prestige associated with it are viewed as the most important
dimensions in the career decision-making process. People begin to narrow their
range of occupations based on their estimates of compatibility (sex-type, prestige,
and interests) and accessibility. Thus, using these three variables and their knowledge
about the accessibility of careers, individuals develop a zone of acceptable
occupations within their cognitive map of the occupational structure (Brown, 2003;
Osipow, 1996). Gottfredson‟s theory provides several concepts about boundaries and
motivational dimensions regarding the formation of occupational aspirations. On the
other hand, Brown (1996) claimed that the propositions relating to the factors that
lead to circumscription and compromise are too general.
29
Krumboltz’s Learning Theory of Career Counseling is an extension of the earlier
Social-Learning Theory Approach to Career Decision Making (Mitchell &
Krumboltz, 1996). “The theory is an attempt to simplify the process of career
selection and is based primarily on life events that are influential in determining
career selection," (Zunker, 2002, p. 65). Krumboltz‟s Learning Theory of Career
Counseling composed of two parts. The first part explains the origins of career
choice and the second part focuses what career counselors can do to help solve
career-related problems (Niles & Hartung, 2000). The theory identified four factors
that influence the career decision-making which are genetic endowment (e.g., race,
sex, physical ability) and special abilities (e.g., intelligence, musical ability, artistic
ability), environmental conditions and events (e.g., number and nature of job
opportunities, social policies and procedures for selecting workers, technological
developments), learning experiences (e.g., instrumental learning experiences,
associative learning experiences), and task approach skills (e.g., work habits,
perceptual and cognitive processes, emotional responses) (Krumboltz, Mitchell, &
Jones, 1976; Krumboltz & Nichols, 1990). As a result of the combination of these
factors three important consequences are postulated. The first is self-observation
generalizations. These are self-views that the individual learns based on life
experiences. The second consequences stresses the task approach skills which
include the both cognitive and affective sets of skills the individuals have developed
such as problem-solving skills, work habits, emotional responses, and cognitive
responses. The last consequences are actions concerned with entry behaviors which
represent an overt step in a career progression including changing a college major,
30
applying for a specific job, accepting a job offer and other activities (Brown, 2003;
Krumboltz et al., 1976; Osipow, 1996). The planned happenstance model (Mitchell,
Levin, & Krumboltz, 1999) was generated to emphasize the role of chance in career
planning. More specifically, the model includes the creating and transforming of
unplanned events into learning opportunities. The goal of a planned happenstance
intervention is to assist client to generate, recognize, and incorporate chance events
into their career development (Mitchell et al., 1999). Accordingly, a four-step
intervention model was proposed as normalized planned happenstance in the client‟s
history, assist clients to transform curiosity into opportunities for learning and
explorations, teach clients to produce desirable chance events, and teach clients to
overcome blocks to action. Strength of the theory is that it considers both
environmental and intra-individual variables affecting career development (Niles &
Harris-Bowlsbey, 2005). In contrast, some negative aspects of the theory are
recognized. According to Brown (1990), the biggest weakness of the theory is its
failure to account for job change. In addition, Osipow and Fitzgerald (1996) argue
that there is too much emphasis on the choice itself and not enough on the adjustment
process.
2.1.2 Emerging Theories of Career Choice and Development
Cognitive Information Processing Approach (CIP) was developed to understand how
people make a career decision and use information in career problem solving and
decision making (Peterson, Sampson, & Reardon, 1991). There are four assumptions
underlying the Career Information Processing Theory. First, career problem solving
31
and decision-making involve the interaction of affective and cognitive processes.
Second, the capability for career problem solving depends on the availability of
cognitive operations and knowledge. Third, career development is ongoing and
cognitive structures such as schemas that develop and grow throughout the life span.
Fourth, enhancing information processing skills is the goal of career counseling.
(Niles & Harris-Bowlsbey, 2005; Peterson, Sampson, Lenz, & Reardon, 2002; Sharf,
2006). In CIP theory, a problem is defined as “a gap between an existing and a
desired state of affairs or more simply, a gap between where a person is and where he
or she wants to be” (Sampson, Lenz, Reardon, & Peterson, 1999, p. 5). The theory
viewed career problem solving is mostly a cognitive process that can be improved
through the communication, analysis, synthesis, valuing, and execution (CASVE)
cycle (Sampson et al., 1999). A choice viewed as the outcome of the problem solving
process. Sampson, Peterson, Lenz and Reardon (1992) proposed a pyramid named as
Pyramid of Information Processing Domains that can be used to show what is
involved in making a career decision. The pyramid includes self-knowledge (e.g.,
values, interest, skills) and occupational knowledge (e.g., occupations, programs of
study, jobs), decision-making skills (e.g., CASVE cycle), and metacognitions (e.g.,
self-talk, self-awareness, and the monitoring and control of the decision-making
process) (Sampson et al., 1999). Therefore, knowledge of self and occupations form
the foundation of pyramid, and then decision making skills and metacognitions
construct on this foundation. CIP approach suggested a career counseling model
composed of seven steps. These steps can be summarized as initial interview,
preliminary assessment, defining problem and analyzing causes, formulating goals,
32
developing individual learning plan, and practicing individual learning plan (Zunker,
2006).
Brown’s Values-Based, Holistic Model of Career and Life-Role Choices and
Satisfaction is a model of career development that focuses on the importance of
values in career decision-making (Niles & Harris-Bowlsbey, 2005). The approach
considered the work of Rokeach (1973), Super (1990), and Beck (1987). Values are
beliefs that are experienced by the individual as standards by which people evaluate
their own actions and the actions of others, and they play a significant role in the
establishment of personal goals. Values are beliefs containing cognitive, affective
and behavioral dimensions (Brown, 2003). According to Brown (2002), values are
shaped by genetics and environment. As a result of genetics and environmental
effects, specific values become more important than others. Brown‟s values-based
model of career choice is based on six basic propositions. First, individuals prioritize
only a small number of values. Second, highly prioritized values are the most
important determinants of life-role choices. Third, values are acquired through
learning from values-laden information in the environment. Forth, life satisfaction
depends on life roles that satisfy all essential values. Fifth, a role‟s salience is related
to degree of satisfaction of essential values within roles. Sixth, success in life role
depends on many factors, some of them are learned skills and some of them are
cognitive, affective, and physical aptitudes (Zunker, 2002). According to approach,
to make a career decision, values should be crystallized and prioritized. Otherwise,
values can be clarified and changed by the processes of contemplation and conflict
33
by means of activities or assessments and self-confrontation of various values (Niles
& Harris-Bowlsbey, 2005).
Ecological Approach of Career Development views human behavior results from the
ongoing dynamic interaction between the person and environment (Cook, Heppner,
& O‟Brien, 2002). Ecological system and person-in-environment are often used
interchangeably (Cormier & Nurius, 2003). In this perspective, four subsystems
were identified which influence human behaviors (Bronfenbrenner, 1977). The first
one is the microsystems include the interpersonal interactions within a given
environment such as home, school, or work settings, the second one is the
mesosystems constitute interactions between two or more microsystems such as the
relations between an individual‟s school and work environment, the third one is the
exosystems consist of linkages between subsystems that indirectly influence the
individual such as neighbors, workplaces, media, and the last one named as
macrosystems that are the ideological components of a given society, including
norms and values (Cook et al., 2002). As the name of the perspective implies, career
development is thought to be influenced and constructed by the interrelationships
between the subsystems in a larger ecosystem (Bronfenbrenner, 1977; Zunker, 2006).
The model also recognizes that although individuals of the same biological sex or
race may encounter similar circumstances because of their demographics, each career
path is unique because of individual circumstances, and unique interactions of their
subsystems (Gysbers et al., 2002).
34
Career Construction Theory “explains the interpretive and interpersonal processes
through which individuals impose meaning and direction on their vocational
behavior” (Savickas, 2005, p. 42). The theory updates and advances Super‟s theory
of vocational development by using the psychological approach of constructivism as
a metatheory with which reconceptualize central concepts of vocational development
theory (Savickas, 2005; Zunker, 2006). Career construction theory addresses how the
career world is made through personal constructivism and social constructionism. It
asserts that individuals construct their own reality. According to Savickas (2005),
individuals construct their careers by imposing meaning on their vocational behavior
and occupational experiences. There are three central components which are
vocational personality, career adaptability, and life themes structure (Amundson et
al., 2009). In addition, goals of the approach can be summarized as to make the client
aware of significant life themes and unresolved problems, to help the client construct
a career that will facilitate the use of this life theme or help solve this unresolved
problem, to help the client develop career adaptability in order to be able to cope
with the ever-changing ways to implement self-concept in work (Amundson et al.,
2009; Niles & Harris-Bowlsbey, 2005).
2.2 Theoretical Framework of the Study: Social Cognitive Career Theory
(SCCT)
Social Cognitive Career Theory (SCCT; Lent, Brown, & Hackett, 1994) is one of the
recent approaches to understand career development processes. It is intended to offer
a unifying framework for bringing together common pieces, or elements, identified
35
by previous career theories such as trait-factor, developmental and work adjustment
and “arranging them into a novel rendering of how people (1) develop vocational
interests, (2) make (and remake) occupational choices and, (3) achieve varying levels
of career success and stability” (Lent, 2005, p. 101).
SCCT is derived primarily from Bandura‟s (1986) general social cognitive theory
which emphasizes the interactions among people, their behavior, and environments.
More specifically, the theory based on two extensions of Bandura‟s theory, which are
Krumboltz and colleagues‟ social learning theory of career decision-making and
Hackett and Betz‟s (1981) career decision-making self-efficacy theory (Lent, Brown,
& Hackett, 1996).
SCCT recognizes the importance of interests, abilities, and values in the career
development process as trait-factor theories. In addition, similar to developmental
theories, SCCT is interested in how people deal with particular developmental
milestones (e.g., career choice) and obstacles (e.g., prematurely eliminated options)
which have an important impact on their career futures. In general, trait-factor,
developmental and social cognitive approaches are concerned with the prediction and
understanding of career development (Lent & Savickas, 1994). Although Social
Cognitive Career Theory shares certain features and goals with the trait-factor and
developmental approaches, it differs in many ways. Unlike the trait-factor theories,
SCCT emphasizes dynamic and situation-specific aspects of both people and their
environments. In contrast to developmental theories, SCCT does not consider the
36
specified ages and stages of career developmental tasks rather, it is concerned with
particular theoretical elements which support effective career behaviors (Lent, 2005).
The theory is predominantly concerned with the roles of three social cognitive
mechanisms related to career development: self-efficacy beliefs, outcome
expectations, and personal goals (Lent et al., 1994; Lent, 2005). Self-efficacy beliefs
refer to “people‟s judgments of their capabilities to organize and execute courses of
action required to attain designated types of performances” (Bandura, 1986, p. 391).
These beliefs are viewed as the most important determinants of thought and action in
Bandura‟s (1986) theory. Self-efficacy beliefs introduced into the career literature by
Hackett and Betz (1981) have received considerable research attention. SCCT is
closely linked to Taylor and Betz‟s (1983) application of the self-efficacy beliefs
which have been found to be predictive of academic and career–related choice and
performance indices (e.g., Hackett & Lent, 1992). These beliefs about personal
capabilities can be changed and responded to environmental conditions. Four
informational sources or types of learning experience may be influence on self-
efficacy beliefs: personal performance accomplishments, vicarious learning, social
persuasion, and physiological and affective states (Bandura, 1997; Lent, 2005). As
stated by Lent (2005), “the impact of these four informational sources on self-
efficacy depends on a variety of factors, such as how individuals attends and
interprets them” (p. 104).
37
Another important component in SCCT is outcome expectations “refer to beliefs
about the consequences or outcomes of performing particular behaviors” (Lent,
2005, p. 104). “Outcome expectations involve imagined consequences of performing
particular behaviors such as if I do this, what will happen?” (Lent et al., 1994, p. 83).
According to Bandura (1986), both self-efficacy and outcome expectations play an
important role to determine the behaviors, however, self-efficacy is seen as more
influential determinant of behavior. People develop outcome expectations about
different academic and career path from a variety of direct and vicarious learning
experiences and secondhand information they obtain about different career fields.
Social cognitive theory suggests that goals have an important role in the self-
regulation of behavior. Accordingly, personal goals are defined as “an individual‟s
intention to engage in a particular activity or to produce a particular outcome,
addressing questions such as, how much and how well do I want to do this?” (Lent,
2005, p. 105). SCCT differentiates choice-content goals (the type of activity or career
the individual wishes to pursue) and performance goals (the level or quality of
performance the individual plans to achieve within a chosen endeavor). By setting
personal goals, people organize, direct, and sustain their own behavior, over long
periods of time even in the absence of external reinforcement. Such goals can be
broadly conceptualized as career plans, decisions, aspirations, and expressed choices
(Lent et al., 1994). According to social cognitive theory, people‟s choice and
performance goals are extremely affected by their self-efficacy and outcome
expectations. For example, low self-efficacy may directly limit the expression of
38
certain choice goals and may be related to increased vocational indecision (Taylor &
Popma, 1990).
SCCT is comprised of three interlocking models (Figure 2.1): (1) the formation of
career interests, (2) selection of academic and career choice options, and (3)
performance in educational and occupational pursuits (Lent et al., 1994). In each
model, “the basic theoretical elements which are self-efficacy, outcome expectations,
and goals are seen as operating in concert with other important aspects of persons
(e.g., gender, race/ ethnicity), their contexts, and learning experiences to help shape
the contours of academic and career development” (Lent, 2005, p. 106).
According to SCCT‟s interest model, self-efficacy and outcome expectations
regarding particular activities help to shape career interests. Interest in activity is
mostly increase when people (1) view themselves as competent regarding the activity
and (2) anticipate positive outcomes. Conversely, when people doubt about their
efficacy and expect undesirable or negative outcomes, they are likely to develop
disinterest to such activities (Lent, 2005; Lent & Brown, 1996; Lent et al., 1994).
Thus, interest, self-efficacy, and positive outcome expectations in relation to a
particular activity are hypothesized to support goals for further activity (Lent &
Brown, 1996). Along with self-efficacy beliefs and outcome expectations, SCCT
considers other aspects of people and their environments which may have an effect
on interests. Each person receives certain affordances from the environment that
assist to form or guide his or her career development (Vondracek, Lerner, &
39
Schulenberg, 1986). In SCCT, these contextual affordances are divided into two
general types, based on when they occur within the choice process. The first type
includes background influences (e.g., cultural and gender role socialization, types of
available career role models) that help to shape self-efficacy, outcome expectations,
and interests. The second type involves environmental influences that come into play
during the active phases of choice-making (e.g., emotional or financial support for
pursuing a particular option). In SCCT‟s interest model, effects of contextual
variables on self-efficacy and outcome expectations are considered. Lent et al.,
(1994) consider two means by which contextual factors may affect people during the
process of setting and implementing their career choice goals. First, SCCT asserts
that some situations may directly influence people‟s choices or implementation
possibilities. For example, in some cultures, individuals may defer their career
decisions to significant others in the family, even where the others‟ preferred career
path is not all that interesting to the individual. Second, contextual variables may
affect people‟s ability or willingness to translate their interests into goals and their
goals into actions. According to SCCT, “career interests are more likely to blossom
into goals (and goals are more likely to be implemented) when people experience
strong environmental supports and weak barriers in relation to their preferred career
paths” (Lent, 2005, p. 110).
According to the choice model of SCCT, career choice is realized by subprocesses as
the development of self-efficacy, outcome expectations, interests, and skills in
different performance domains. After initial career choices are made, they are subject
40
to future revisions because people and their environments are dynamic. Therefore,
new paths (or branches from old paths) may occur, barriers may arise, or value and
interest priorities may shift during the individual‟s working life (Lent, 2005). It is
assumed that “under supportive environmental conditions, people‟s career interests
tend to orient them toward particular fields wherein they might perform preferred
activities and might interact with others who are like themselves in important ways”
as in Holland‟s theory (Lent & Brown, 1996, p. 315). There are many factors lead to
construction of choice such as economic realities, family dictate and wishes,
discrimination, or the quality of one‟s prior education. Thus, career choice may be
less an expression of personal interests than of other factors (Lent, 2005; Lent &
Brown, 1996; Lent et al., 1994).
In the performance model, SCCT is mainly concerned with the factors which
influence academic and career related performance. SCCT views educational and
vocational performance as involving the interaction among people‟s ability, self-
efficacy, outcome expectations, and performance goals. Accordingly, stronger self-
efficacy and positive outcome expectations support more motivated goals, which
help to organize and sustain performance efforts. Although this model points person-
level (e.g., cognitive, motivational) processes, people develop their talents, self-
efficacy, outcome expectations, and goals within a larger sociocultural context. “The
learning experiences to which people are exposed and the performance outcomes
they receive are intimately related to features of their environments, such as
educational quality, nature of available role models, parenting style, gender role
41
socialization, peer supports, and community and family norms” (Lent, 2005, p. 112).
Moreover, self-efficacy is seen as complementing objectively assessed ability in
SCCT‟s performance model. For example, individuals with low confidence in their
abilities to complete career decision-making tasks may exhibit increased career
indecision (Taylor & Betz, 1983).
SCCT also takes into account personal, environmental, and societal factors that
indirectly influence interest formation and career choice behaviors. According to
Lent et al. (1994), person inputs refer to biological attributes, such as race and sex
that impact the individual through his or her social/cultural meaning. Other person
inputs include ability and predispositions such as personality. Within the SCCT
models two types of contextual influences are posited, (1) background contextual
affordances that directly precede learning experiences and (2) contextual influences
proximal to career choice. Learning experiences are conceptualized as the four
sources of self-efficacy proposed by Bandura (1986): performance accomplishments
(one‟s own successes or failures in particular activities), verbal persuasion (career-
related messages received from important others), vicarious learning (influence of
observing others‟ behaviors and outcomes), and psychological affective states
(emotional arousal that influences one‟s cognitions regarding career-related
information). According to SCCT, these experiences are posited to influence self-
efficacy and outcome expectations. Person inputs, learning experiences, and
contextual influences are hypothesized to influence career choice and behaviors
through three possible pathways: “(a) precursors of sociocognitive variables, (b)
42
moderators of certain key theoretical relations, or (c) direct facilitators or deterrents”
(Lent et al., 1994, p. 101). Background contextual affordances include family and
social inputs that shape learning experiences, whereas contextual influences proximal
to choice behaviors include factors such as career opportunities and barriers.
43
Fig
ure
2.1
Model
of
per
son, co
nte
xtu
al, an
d e
xp
erie
nti
al f
acto
rs a
ffec
ting c
aree
r-re
late
d c
hoic
e beh
avio
r.
Copyri
ght
1993 b
y R
. W
. L
ent,
S. D
. B
row
n, an
d G
. H
ack
ett.
Rep
rinte
d b
y p
erm
issi
on.
44
SCCT has received considerable research attention since its introduction. The
theory‟s basic predictions regarding interest, choice and performance have been
supported by a number of studies. However, studies of SCCT have largely focused
on mathematics and science-related fields rather than academic/ career domains
(Lent, Brown, Nota, & Soresi, 2003). A selective review of studies that point out
career decision making and related factors within the framework of SCCT presented.
In one such study, Huang (1999) designed a mediational model based on SCCT that
incorporated four constructs: family environment (family relationship), personality
(neuroticism, extraversion, openness, agreeableness and conscientiousness), self-
efficacy (technical-scientific self-efficacy and aesthetic self-efficacy), and career
indecision (chronic indecision, developmental indecision, and global indecision) in a
group of university students (N = 268). This investigation emphasized the role of
self-efficacy as a mediator as in SCCT. Consistent with SCCT, results of the study
revealed that family environment and personality were related to men‟s career
indecision directly and indirectly through self-efficacy. Further, personality is a
personal input related to women‟s career indecision directly and indirectly mediated
by self-efficacy.
Similarly, in a more recent study, Feldt and Woelfel (2009) examined gender,
personality domains of five-factor model, and anticipated career outcomes through
SCCT to determine predictors of career indecision among 179 college students.
Results indicated that gender; five-factor domains of neuroticism, agreeableness,
45
conscientiousness and outcome expectations were significant predictors of career
indecision.
In another study, Tang, Fouad, and Smith (1999) investigated the role of
acculturation, family socioeconomic status, family involvement, occupational
interests and career self-efficacy on career choice of Asian American college
students (N = 187) by utilizing SCCT. As a result, Asian Americans were influenced
by acculturation, family background, and self-efficacy in choosing occupations.
More recently, Rogers, Creed, and Glendon (2008) designed a study to extend the
SCCT choice model to the domain of career decision-making and test how
personality and social support contribute to the career readiness actions of career
planning and exploration. Overall findings of the study indicated that personality and
supports are related to the career choice process both directly and indirectly.
In order to test interest and choice hypotheses of SCCT, Lent et al. (2003) conducted
a study that included self-efficacy, outcome expectations, interests, social supports
and barriers, and choice consideration related to occupations representing Holland‟s
(1997) six RIASEC types in a sample of 769 Italian high school students. Results
indicated general support, across Holland types, for the hypotheses that self-efficacy
and outcome expectations jointly predict interests, and that interests mediate the
relations of self-efficacy and outcome expectations to choice consideration. In
46
contrast to predictions of SCCT, social supports and barriers related to choice
consideration indirectly through self-efficacy rather than directly.
Constantine, Wallace, and Kindaichi (2005) examined the degree to which African
American high school students‟ (N = 151) perceptions of career barriers and parental
support predicted their career certainty and career indecision based on SCCT.
Accordingly, perceived occupational barriers were positively predictive of career
indecision, and perceived parental support was positively related to career certainty.
Results confirmed the hypotheses of SCCT regarding contextual variables in the
career decision-making process.
Another partial test of applicability of SCCT to career choice behavior was
performed to evaluate the influence of personal and contextual factors on career
decision making process (Weiss, 2000). More specifically, aim of the study was to
clarify the role of career decision-making self-efficacy, career outcome expectations,
and perceived career barriers on career indecision in a sample of college students (N
= 460). Findings of the study revealed that lower career decision-making self
efficacy was found to be associated with both increased career indecision and greater
perceived barriers. Higher perceived barriers were also related to increased career
indecision. Thus, career decision-making self-efficacy and perceived barriers were
found to significantly predict career indecision across the overall sample.
Consequently, it can be inferred that aforementioned results of the studies mostly
47
provide support for the utility of SCCT in understanding career decision making
process as well as career choice behavior.
2.3 Demographic Variables and Career Indecision
Many studies have investigated demographic variables in relation with career
indecision. Thus, the relationships with such demographic variables as gender, age,
grade levels and academic achievement were more commonly examined by the
construct of career indecision along with many intra-personal and interpersonal
variables.
Among demographics, gender is more frequently investigated variable. Even though
studies that evaluated gender difference have repeatedly reported no difference on
career indecision (Browne, 2005; Creed, Patton, & Prideaux, 2006; Guerra &
Braungart-Rieker, 1999; Kang, 2009; Osipow, Carney, & Barak, 1976; Taylor, 1982,
Weiss, 2000), a small number of them have shown that females have experienced
higher career indecision than males (e.g., Creed, Patton, & Bartrum, 2004; Turkson,
2003). For example, a study conducted with high school students revealed that senior
high school female students had significantly higher mean score on Career Indecision
Subscale of Career Decision Scale than male students (Creed et al., 2004).
Studies investigating the role of age on career indecision have consistently found a
negative relation between age and career indecision. For example, Ng and Feldman
(2009), as a part of their study, examined the correlation between age and career
48
indecision among Chinese college students and reported a moderate negative
correlation. In addition, Rohner, Rising, and Sayre-Scibona (2009) reported a
significant correlation between career indecision and age of the female participants in
the negative direction. Results regarding negative relationship between age and
career indecision (e.g., Kinnier, Brigman, Noble, 1990; Peng & Herr, 2002)
consistent with theoretical arguments which have stressed on developmental stages
and career maturity (Crites, 1978; Super, 1957). In contrast to studies reported
negative correlation between age and career indecision, few of the findings presented
no significant relationship between them (e.g., Abu Talib & Kit Aun, 2009).
Naturally, it should be considered that age and grade level are likely to be highly
correlated. Thus, results of studies investigated the association between grade levels
and career indecision similar to results of the studies examined the relationship
between age and career indecision like younger students reported higher career
indecision than older students (e.g., Guerra & Braungart-Rieker, 1999; Peng & Herr,
2002).
In general, academic achievement was evaluated by means of cumulative grade point
average (CGPA). With regard to academic achievement, as concluded Hall and Kelly
(1995) results of the studies seemed to be contradictory. For example, Osipow and
Waddell (1980) reported a negative correlation between career indecision and grade
point average in a sample of college students (as cited in Osipow, 1987). Likewise,
Daggit (1996) supported a negative relationship between CGPA and career
indecision. On the other hand, more recent studies found a positive correlation
49
between CGPA and career indecision (e.g., Abu Talib & Kit Aun, 2009). Thus, it
does not possible to make a constant conclusion about the influence of academic
achievement on career indecision.
2.4 Factors Contributing to Career Indecision
An extensive amount of research has been conducted to expand the understanding of
career indecision and its contributing factors. Therefore, numerous intra-individual
and interpersonal factors have been found to influence career indecision like locus of
control (e.g., Ng & Feldman, 2009; Saunders, 1997; Taylor, 1982; Taylor & Popma,
1990), trait and state anxiety (e.g., Corkin, Arbona, Coleman, & Ramirez, 2008;
Fuqua, Seaworth, & Newman, 1987), decision-making styles (e.g., Mau, 1995;
Osipow & Reed, 1985), hope (e.g., Woodbury, 1999), self-esteem (e.g., Emmanuelle,
2009; Germeijs & De Boeck, 2002), fear of commitment (e.g., Leong & Chervinko,
1996), depression (Saunders, Peterson, Sampson, & Reardon, 2000), irrational
beliefs (e.g., Stead, Watson, & Foxcroft, 1993), perfectionism (e.g., Leong &
Chervinko, 1996; Page, Bruch, & Haase, 2008), identity formation (e.g., Guerra &
Braungart-Rieker, 1999). Personality is also one of the concepts researchers have
studied when considering factors affecting career indecision. Personality traits are
generally operationalized by the Big Five traits of neurotism, extraversion, openness
to experience, agreeableness and conscientiousness (e.g., Feldt & Woelfel, 2009;
Page et al., 2008).
50
Such family factors on career indecision have been investigated as parental
attachment (e.g., Emmanuelle, 2009), psychological separation (e.g., Santos &
Coimbra, 2000; Tokar, Withrow, Hall, & Moradi, 2003), perceived family conflict
(e.g., Constantine & Flores, 2006), family relationship (e.g., Constantine & Flores,
2006; Dodge, 2001; Guerra & Braungart-Rieker, 1999), and perceived parental
support (e.g., Constantine, Wallace, & Kindaichi, 2005; Nota, Ferrari, Solberg, &
Soresi, 2007).
In addition, many career related factors like vocational maturity (e.g., Creed,
Prideaux, & Patton, 2005), career decision making self-efficacy (e.g., Betz & Klein-
Voyten, 1997; Taylor & Popma, 1990), career salience (e.g., Taylor & Popma,
1990), career outcome expectations (e.g., Betz & Klein-Voyten, 1997; Feldt &
Woelfel, 2009), dysfunctional career thinking (e.g., Saunders et al., 2000), fear of
success (e.g., Staley, 1996; Taylor, 1982), vocational self-concept (e.g., Tokar et al.,
2003), career aspiration (e.g., Constantine & Flores, 2006), perceived career barriers
(e.g., Constantine et al., 2005), and career certainty (e.g., Constantine & Flores,
2006) contributed to career indecision to some extent.
2.5 Research on Proposed Model Variables
As a result of literature review, it is possible to conclude that multiple factors
contribute to career indecision to some extent. Accordingly, a set of variables was
selected for the inclusion in the proposed path model has been identified as the
51
significant factors to explain the career indecision as well as the major constructs of
the SCCT as self-efficacy and outcome expectations.
The following part of the literature review will summarize many research findings on
career indecision and the study variables. In the present study, locus of control and
parental attitudes (acceptance/ involvement, psychological autonomy, strictness/
supervision) were regarded as exogenous variables which were not predicted by any
other study variables. Career decision-making self-efficacy and career decision-
making outcome expectations were regarded as endogenous variables which were
predicted by at least one study variable.
2.5.1 Locus of Control and Career Indecision
Aforementioned, locus of control viewed as one of the central and reliable predictors
of the career decision process and career development of college students (Brusoski,
Golin, Gallagher, & Moore, 1993; Luzzo & Ward, 1995). Taylor (1982) explained
the role of locus of control in the career development process as
individuals perceiving an internal locus of control tend to view themselves as
having more control over and personal responsibility for the direction of their
lives than do externals, who are likely to feel themselves powerless to control
events. Thus, internally locused individuals may take both an active role in
the direction of their educational/ vocational futures and personal
52
responsibility for decision making and for gathering the kinds of information
necessary to such decisions. Externals, on the other hand, may believe that
vocational plans are largely influenced by chance factors and thus fail to
invest time and energy in information-gathering and vocational decision-
making activities. (Taylor, 1982, p. 319-320)
Findings of the Taylor‟s (1982) study that investigated the relationships among locus
of control, fear of success and vocational indecision in a group of 201 undergraduate
students showed a positive relationship between external locus of control and career
indecision. Thus, vocationally undecided students were found to be more external in
their locus of control than decided students.
In another study, Woodbury (1999) demonstrated similar findings by examining the
relationship of anxiety, locus of control, hope and career indecision among 244
African American university students. Results of the correlational analysis revealed
that both external dimensions of locus of control, powerful others and chance were
significantly correlated with career indecision.
Likewise, Saunders (1997) reported a positive and significant correlation between
external locus of control and career indecision in a group of 215 undergraduate
students.
53
In a sample of graduate students (N = 207), Simon (1990) investigated the
association among locus of control, career concepts and career indecision. Results
verified the previous findings in the similar vein as career undecided graduate
students are more external in their locus of control than career decided students.
Consequently, previous studies carried out with different samples have consistently
revealed similar findings as external locus of control is related to career indecision in
a positive manner.
2.5.2 Parental Influence on Career Indecision
The career development literature acknowledges the influence of parents on career
development of adolescents and young adults (Osipow, 1983; Roe, 1957; Super,
1957). For instance, Lopez and Andrews (1987) have conceptualized career
indecision as “the outcome of a larger set of transactions between the person and the
family” (p. 65). Accordingly, many researchers emphasized the importance of
determining the role and influence of parents to understand the complexities of
career development (e.g., Vondracek, Lerner, & Schulenbergerg, 1986). The
influence of several parental variables such as parenting styles, parental attachment,
parental autonomy, and parental support etc. on individuals‟ career development has
gained the interest of several researchers.
54
In their partial examination of Social Cognitive Career Model (Lent et al., 1994),
Ferry, Fouad, and Smith (2000) investigated the parental variables included
encouragement; one of the indicator of parental involvement and control; one of the
parenting style as background contextual variables. Results on a sample of 791
undergraduate students showed that parental encouragement in math and sciences
was found to be significantly effective in learning experiences. In contrast, parental
control did not lead to any significant path.
Guerra and Braungart-Rieker (1999) investigated parental (both maternal and
paternal) acceptance and encouragement of independence as predictors of career
indecision in a group of 169 undergraduate students. Overall results of the study
indicated that mother‟s encouragement of independence was a significant predictor
of career indecision. Thus, less maternal encouragement of independence lead to
more career indecision. On the other hand, other parental variables as mother‟s
acceptance, father‟s acceptance, and father‟s encouragement of independence did not
have any significant contribution on career indecision.
In another study conducted by Huang (1999) investigated the utility of Lent et al.‟s
(1994) Social Cognitive Career Theory to understand the career indecision by means
of structural equation modeling. In this study, family relationship (cohesion and
expressiveness) and family structure (independence and control) variables were
considered in the background context of proposed model. The sample of the study
consisted of 268 university students. Two separate models were tested for male and
55
female students. According to the results of the study, family relationship and family
structure did not have any direct effect on career indecision for females. In contrast
to results of the female sample, there was a direct effect of family relationship on
chronic indecision and a direct effect of family structure on developmental indecision
observed among males.
Tokar, Withrow, Hall, and Moradi (2003) investigated the role of psychological
separation and attachment security variables in students‟ experience of career
indecision using structural equation modeling. Results of this study based on a
sample of 350 university students revealed that some components of separation and
attachment security related to career indecision. Accordingly, two of the six
predictors, attachment anxiety and maternal separation, had significant relationships
with all three indecision constructs. In addition, maternal conflictual independence
was significantly related to both indecision constructs that include chronic
components (i.e., career indecisiveness and global indecision). Finally, paternal
separation had a significant and negative relationship with the career indecisiveness
construct.
Constantine, Wallace, and Kindaichi (2005) explored the role of perceived parental
support and perceived occupational barriers on both career indecision and career
certainty in a group of 151 high school students using Social Cognitive Career
Theory as a framework of their study. Their results revealed that perceived parental
support was a positive significant predictor of career certainty but not for career
56
indecision. On the other hand, perceived career barriers were significantly related to
career indecision but not related to career certainty.
Kinnier, et al. (1990) conducted a study to understand the role of enmeshment which
refers to “a familial environment in which members are undifferentiated from or
overly dependent on each other” (Minuchin, Montalvo, Guerney, Rosman, &
Schumer, 1967, as cited in Kinnier et al., 1990, p. 309) on career indecision (N =
604). Accordingly, significant negative relationship was found between career
indecision and individuation. Hence, more decided students tended to be more
individuated.
Santos and Coimbra (2000), analyzed the association between psychological
separation, developmental career indecision and generalized indecision.
Psychological separation from mother and father was evaluated as conflictual
independence and emotional independence. The research was carried out by 418
senior high school students. The correlation analyses among the studied variables
showed significant and positive relationships between developmental career
indecision and emotional independence from mother and father. Other significant
positive relationships were observed between generalized indecision and conflictual
independence from mother and father and emotional independence from mother.
Guay, Ratelle, Senécal, Larose, and Deschênes (2006) designed a three-year
longitudinal study with college students (N = 325) to test the validity of two types of
career indecision (developmental and chronic) over time and to investigate such
57
correlates of these types of indecision as self-efficacy, autonomy, control and
autonomy support from parents and friends. Overall, results of the study indicated
that individuals in the decided group were more autonomous and perceived less
control from peers and parents as well as more autonomy support from peers than
individuals in the chronically undecided group. Developmentally undecided
individuals also reported higher levels of perceived autonomy than individuals in the
chronically undecided group. In addition, there was no difference on perceived
autonomy between the decided and developmentally undecided groups.
In a more recent study, Rohner, Rising, and Sayre-Scibona (2009) examined the
relationship between career indecision, self-reported psychological adjustment, and
remembrances of maternal and paternal acceptance and behavioral control in
childhood with respect to gender. Participants were 126 undergraduate students.
Specifically, they found that remembered parental (both maternal and paternal)
acceptance in childhood and current psychological adjustment of females were
significantly and positively associated with career indecision, but not males.
Moreover, no relationship was obtained between remembered parental (both
maternal and paternal) control in childhood and career indecision among males and
females.
Although the importance and influential role of the family, more specifically parents
on career development has been emphasized by some of the traditional theories of
58
career development (Roe, 1957; Super, 1957), the results of the studies examining
parental influences on career indecision seems somewhat mixed.
2.5.3 Career Decision Making Self-Efficacy and Career Indecision
A person‟s beliefs about his or her ability to successfully perform a given task or
behavior termed as self-efficacy beliefs which are seen as mediators between
behavior and behavior chance (Bandura, 1977).
Efficacy expectations determine whether or not behavior will be initiated,
how much effort will be expended, and how long behavior will be sustained
in the face of obstacles and aversive experiences. Efficacy expectations, and
their consequences, vary on dimensions of level, strength, and generality.
Level refers to the degree of difficulty of tasks the individual feels capable of
attempting. Strength refers to the durability of efficacy expectations when the
individual is confronted with disconfirming or dissuading experiences.
Generality involves the degree to which expectations of personal efficacy
transfer to different behavioral domains. (Hackett & Betz, 1981, p. 328)
After Betz and Hackett‟s (1981) pioneering work, career decision-making self-
efficacy has been mostly investigated with career indecision by several researchers.
For example; Taylor and Popma (1990), in a study of 407 college students, examined
the relationship among career decision-making self-efficacy, career salience, locus of
control, and career indecision. They reported a moderate negative relationship career
59
decision-making self-efficacy and career indecision and noted that the only variable
to make a significant contribution to the prediction of career indecision was career
decision-making self-efficacy.
Mathieu, Sowa and Niles (1993) examined career decision-making self-efficacy and
career indecision in a study of 101 college females. They found that women who
were undecided about their occupational choice scored lower on measures career
decision-making self-efficacy than women expressed a preference for a
nontraditional or gender-neutral occupation.
Gillespie and Hillman (1993) found a negative relationship between career decision
making self-efficacy and career indecision among 224 high school students. In
addition, they reported that as self-efficacy for performing tasks associated with
career decision making increased, career indecision decreased.
Another study was conducted by Betz and Klein-Voyten (1997) aimed to examine
the extent to which career decision-making efficacy and outcome expectations are
related to career indecision and exploration intentions among a group of 350
university students. The findings of the study revealed a negative correlation between
career outcome expectations and career indecision in men, however, such a
significant correlation did not found in women. In addition, career decision-making
self-efficacy and career outcome are positively correlated both in men and women
sample.
60
Weiss (2000) designed a study to examine gender and racial/ ethnic differences in
perceived career barriers, career decision-making and vocational indecision within
the framework of SCCT in a sample of college students (N = 460). Gender and
racial/ ethnic differences were found in both total barrier scores. Higher perceived
barriers were associated with both career decision-making self-efficacy and greater
vocational indecision. Lower career decision-making self-efficacy was associated
with increased indecision. In addition, career decision-making self-efficacy was
found to be the most effective predictor of career indecision in the SCCT.
Considering the previous research findings, it is possible to conclude that career
decision-making self-efficacy and career indecision have consistently been found to
be negatively correlated.
2.5.4 Career Decision-Making Outcome Expectations and Career Indecision
Another important mediator variable of SCCT as well as the current study is outcome
expectations. “Outcome expectations refer to the belief that, given the performance
of a particular behavior, certain results will follow”. An outcome expectation is thus
“a belief about the consequences of behavior” (Hackett & Betz, 1981, p. 328).
In order to assess outcome expectations and exploratory intentions, Betz and Klein-
Voyten (1997) designed a study aimed to investigate the extent to which career
decision-making efficacy and outcome expectations relate to career indecision and
exploration intentions among university students (N = 350). As a part of this study
61
they developed Career Outcome Expectations and Exploratory Intentions Scale. The
findings of the study showed that the correlations between goal selection and
academic outcome, goal selection and career outcome and total CDMSE score and
career outcome are statistically greater in men than in women. In addition, higher
levels of career decision-making self-efficacy are positively related to exploratory
intentions and are related to lower levels of indecision.
Using the SCCT as a framework, Weiss (2000) was designed a study to examine
gender and racial/ ethnic differences in perceived career barriers, career decision-
making and vocational indecision. A sample of college students (N = 460) completed
the Career Decision Self-Efficacy Scale-Short Form, Career Outcomes Expectations
Scale, Career Decision Scale and Career Barriers Inventory-Revised. Accordingly,
perceived barriers and career decision-making self-efficacy were found significant
predictors of career indecision. However, regression analysis revealed that career
decision-making outcome expectations was not a predictor of career indecision.
Correlations among the study variables showed that no significant relationship
existed between career indecision and career decision-making outcome expectations
in all sample. However, separate correlation analyses for males and females revealed
a significant negative relationship between career indecision and career decision-
making outcome expectations for males, but not for females.
Social cognitive variables of learning experiences in the form of racist and sexist
events in relation to career decision-making self-efficacy, career outcome
62
expectations and career indecision were examined in a group that composed of 108
African American women (Lemon, 2010). Results revealed that career indecision
and career decision making self-efficacy did not correlate significantly. In addition,
career indecision and career outcome expectations did not correlate, too. However, a
significant and positive relationship was reported between career decision-making
self-efficacy and career outcome expectations.
Thus, it is possible to conclude that in the parallel direction of the literature, an
inverse relationship between career decision-making outcome expectations and
career indecision was generally obtained. On the other hand, overall a positive
relationship was reported between career decision-making outcome expectations and
career decision-making self-efficacy.
2.6 Studies on Career Indecision in Turkey
In the last two decade there has been an increase in research on career counseling in
Turkey. Studies in career counseling in Turkey, mostly interested in the concept of
vocational maturity (e.g., Bacanlı, 1995; Evren, 1999; Uskaner, 1999), and factors
that affect the career choice (e.g., AbiĢeva, 1997; Büyükgöze Kavas, 2005; Genç,
Kaya, & Genç, 2007; Köksalan, 1999; Özyürek & Kılıç-Atıcı, 2002). Other
important concepts of career counseling such as career decision-making self-efficacy
(e.g., Bozgeyikli, 2005; Bozgeyikli, Bacanlı, & Doğan, 2009), career search self-
efficacy (e.g., Bacanlı, 2006a), career indecision (e.g., Çakır, 2003; Hamamcı &
63
Hamurlu, 2005), individual and group vocational guidance interventions (e.g., Aydın,
2002; Durlanık, 1998; Efilti, 1998; Öksüz, 2001) and vocational guidance services
(e.g., Koçak, 2001; ĠĢmen Gazioğlu, Bekçi, Yavuz, & Çayırdağ, 2007), career beliefs
(Ulu, 2007), career values (Korkut-Owen et al., 2009) has gained the research
attention in Turkey. More recent studies in the field of career counseling include
career decision-making difficulties of adolescents (Bacanlı, 2008), career decision of
high school students related to their parenting and parent attachment styles
(Cenkseven, Kırdök, & IĢık, 2008), irrational beliefs in career choice of high school
students (Yılmaz Erdem & Bilge, 2008), predictors of career decision making self-
efficacy of 8th
graders (Bozgeyikli, Bacanlı, & Doğan, 2009).
Although there are several investigations with secondary and mostly high school
students, only a small number of studies have been conducted with university
students in the field of career counseling in Turkey. These limited number of studies
(AbiĢeva, 1997; Büyükgöze-Kavas, 2005; Kağnıcı, 1999; Koç, 1991; Köksalan,
1999; Sarıkaya & Khorshid, 2009; Uysal, 2001) generally examined the variables
that affect university students‟ career choice prior to university like high school type,
parents‟ educational level, socioeconomic status, university entrance exam scores,
and career guidance services, etc. In addition, vocational maturity, career
commitment, career development needs, and career values of university student were
examined (Balın, 2008; BektaĢ & Demir, 2004; PiĢkin & Gerçek, 2008; Yerin
Güneri, Owen, Tanrıkulu, Dolunay, & Büyüköze-Kavas, 2009).
64
In contrast to Europe and the U.S. there have been few empirical studies on career
indecision in Turkey and all of them were carried out with high school students. For
example, Çakır (2003) investigated the effect of a 10-week career guidance program
on career indecision levels of high school students. The career guidance program was
developed based on an eclectic approach including developmental approaches, trait-
and-factor approaches, and cognitive information processing approach. In this study,
researcher has developed Career Decision Inventory to assess the first grade high
school students‟ level of career indecision. The results of the study revealed
significant differences between pre-test and post-test scores of the experimental
group subjects (10 male, 9 female). However, no difference was found between the
pre-test and post-test results of the control group (10 male, 9 female).
In a study conducted with 200 high school students and their parents in Gaziantep,
Hamamcı and Hamurlu (2005) examined the relationship between level of
knowledge about career development and attitudes of parents and the help they
provided to their children for career development and career indecision. Thus, study
had two groups of participants as parents and their children. In order to collect data,
Career Development Knowledge Test and Career Development Helping Scale were
administered to parents; Career Decision Inventory was administered to the children.
Results of the study indicated that grade level and receiving career counseling were
found to be the most significant predictors of career indecision. Accordingly,
students who are at higher grade levels and who receive career counseling,
experience less career indecision.
65
The relationship among career indecision, general irrational beliefs, irrational career
beliefs, and vocational maturity of high school students (N = 282) were investigated
by Hamamcı and Esen Çoban (2007). The results of the study revealed that no
significant relationships among irrational beliefs, vocational maturity, and career
indecision. However, high positive correlation between irrational career beliefs and
career indecision was found. Moreover, irrational career beliefs were negatively and
moderately correlated with vocational maturity. The results showed that general
irrational beliefs were not the strong predictor of vocational maturity and career
indecision; however, irrational career beliefs explained 55% of variance of career
indecision and 26% of vocational maturity.
Cenkseven, Kırdök, and IĢık (2008) investigated career decision status of high school
students (N = 382) considering parenting styles and parental attachment. Overall
results of the study demonstrated that students who experienced a medium or high
degree of attachment to their parents were found more decided. In addition, students
from more authoritative and authoritarian families were found more decided than
ones from neglectful and indulgent.
More recently, Kırdök (2010) examined the effectiveness of a career decision
making program, which based on cognitive information processing approach, on
career indecision, irrational career beliefs and vocational maturity level of 9th
grade
high school students. The sample of the study composed of an experiment (15
female, 14 male) and control group (17 female, 13 male). A pre-test post-test
66
experimental research design was followed. Each group session was last 90 minutes
during 10 week. Results indicated significant differences between scores of pre-test
and post-test like that career indecision and irrational career beliefs levels of the
students in experimental group decreased, on the other hand, vocational maturity
level of the students increased.
2.7 Summary
Career indecision has gained researchers attention as a major concern of career
counseling for many years. Many career choice and development approaches have
been generated to explain career development and decision making process. In this
chapter, major theories and models of career choice and development were classified
as emerged and emerging career choice and development theories. Parsons‟ Trait and
Factor Theory, Theory of Work Adjustment, Holland‟s Career Typology, Super‟s
life-span/ life-space theory, Gottfredson‟s Theory of Circumscription and
Compromise, and Krumboltz‟s Learning Theory of Career Counseling were
summarized as emerged theories and Cognitive Information Processing Approach,
Brown‟s Values-Based Holistic Model of Career and Life-Role Choices and
Satisfaction, Ecological Model of Career Development, and Career Construction
Theory were summarized as emerging theories. Social cognitive career theory (Lent
et al., 1994, 2000) is one of the emerging approaches that were utilized as the
framework of the present study. Various studies have been conducted to understand
the factors that contributed to career indecision. Accordingly, numerous intra-
67
individual, interpersonal, and environmental factors have been identified abroad as
significant predictors of career indecision such as anxiety, locus of control, career
decision-making self-efficacy, vocational maturity, career outcome expectations,
personality, parental relationship, psychological separation, parental support. In the
current study, locus of control, perceived parental attitudes (perceived parental
acceptance/ involvement, perceived parental strictness/ supervision, and perceived
parental psychological autonomy), career decision-making self-efficacy, and career
outcome expectations were included to predict career indecision.
68
CHAPTER III
METHOD
This chapter provides information regarding the methodological procedures followed
throughout the study. The chapter starts with explanations about the sampling
procedure and characteristics of the participants. Then, the descriptions of the data
collection instruments are presented by their psychometric properties, reliability and
validity studies. Lastly, data collection and data analysis procedures are presented
along with potential limitations at the end of the chapter.
3.1 Sampling Procedure and Participants
Data were collected during spring semester of 2009-2010 academic year. While
collecting the data, proportional quoata sampling (Trochim & Donnelly, 2007) was
used. Thus it was intended to reach 5 % of the students from each faculty and class.
Accordingly, the METU Activity Report 2008 was considered to determine the
approximate number of the students in each faculty with respect to class. The
participants of the current study were 742 undergraduate students enrolled in five
different faculties at Middle East Technical University (METU). After the data
cleaning procedure 723 participants constituted the sample of the present study.
Participants excluded from the sample were three students from Faculty of
69
Engineering and sixteen students from Faculty of Arts and Sciences. Since, the
number of participants from the Faculty of Arts and Sciences was less than the
predetermined criteria of 5%, the sampling method used in this study could be
regarded as convenience sampling.
Of the 723 participants, 338 (46.7 %) were female, 383 (53%) were male and 2
(0.3%) did not indicate gender. The class was distributed as 225 (31.1 %) freshmen,
160 (22.1 %) sophomores, 169 (23.4 %) juniors, 167 (23.1 %) seniors, and 2 (0.3 %)
of the participants did not report any class. All faculties of METU were represented
in the sample. Out of all participants, 68 (9.4 %) were from Faculty of Architecture,
84 (11.6 %) were from Faculty of Arts and Sciences, 140 (19.4 %) were from
Faculty of Economics and Administrative Sciences, 125 (17.3 %) were from Faculty
of Education, 303 (41.9 %), were from Faculty of Engineering, and 3 (0.4 %)
students did not indicate any faculty. The age of the participants ranged from 17 to
27, with a mean of 21.39 (SD = 1.5). The cumulative grade point average (CGPA) of
the participants was ranged between .59 and 4.00, with a mean of 2.66 (SD = .68).
3.2 Data Collection Instruments
Participants were given a survey package including a short Demographic Information
Form, Career Decision Scale (CDS; Osipow, Carney, Winer, Yanico, & Koschier,
1976), Career Decision Self-Efficacy Scale- Short Form (CDSE-SF; Betz & Klein,
1996; Betz, Hammond, & Multon, 2005), Career Decision-Making Outcome
70
Expectations and Exploratory Intentions Scale (OEX-EI; Betz & Klein-Voyten,
1997), Parental Attitude Scale (PAS; Lamborn, Mounts, Steinberg, & Dornbusch,
1991), and Rotter‟s Internal External Locus of Control Scale (IELCS; Rotter, 1966),
respectively.
3.2.1 Demographic Information Form
To gather basic demographics of the participants, the researcher developed a short
demographic information form which was placed on the first page of the survey
package. The form included questions regarding gender, age, cumulative GPA, class,
faculty, and department or program.
3.2.2 Career Decision Scale (CDS)
Career Decision Scale was developed by Osipow, Carney, Winer, Yanico, and
Koschier (1976) to assess the construct of career indecision. It is a 19 item scale
including an open-ended item. The first 18 items of the scale rating on a four point
Likert type scale as “exactly like me” (4), “very much like me” (3), “only slightly
like me” (2), and “not at all like me” (1). The first two items (1 and 2) form the
Certainty Subscale and the remaining 16 items (3 to 18) constitute the Indecision
Subscale. The last item of the scale was designed as open-ended which offers an
opportunity to participants to list further obstacles for career indecision not
mentioned in the scale items.
71
The scores of the Indecision Subscale range between 16 and 64, with the higher
scores representing higher level of indecision (Osipow, 1987). Possible scores
obtained from the Certainty Subscale range from 2 to 8 and high scores indicate a
high degree of certainty about career decision. The CDS has been widely translated
and adapted to many languages such as French, Hebrew, Korean, Portuguese,
Spanish, and Swedish (Osipow & Winer, 1996).
Osipow et al. (1976, 1987) examined the validity and reliability of the CDS. To
determine the factor structure of the Indecision Subscale, Osipow, Carney, and Barak
(1976) conducted a principal factor analysis with varimax rotation on a sample of
837 university students. Four factors explained the %81.3 of the total variance. These
factors were labeled as “lack of structure and confidence, presence or perception of
some external barriers, approach-approach problem and some kind of personal
conflict regarding how to make the decision” (Osipow et al., 1976, p. 239).
To date various studies have examined the factor structure of the Indecision Subscale
items (items 3 to 18) by using a wide range of extraction and rotation methods. For
instance, Osipow et. al. (1976) performed factor analysis by using principal factor
analysis with varimax rotation, Shimizu, Vondracek, Schulenberg and Hostetler
(1988) used and recommended maximum likelihood extraction with promax
(oblique) rotation and recently principal component analysis with varimax rotation
was used by Corkin, Arbona, Coleman, and Ramirez (2008). At the same time,
confirmatory factor analysis performed by some of the researchers to test the factor
72
structure of the scale (Feldt et al., 2010; Martin, Sabourin, Laplante, & Coallier,
1991; Schulenberg, Shimizu, Vondracek, & Hostetler, 1988). However, majority of
them failed to find the original four-factor structure of the CDS‟s Indecision
Subscale (e.g. Kazdin, 1976; Slaney, Palko-Nonemaker, & Alexander, 1981). In
consequence, findings regarding the factor structure of the subscale far away from
stability and varied from one-factor to five-factor solutions (e.g. Feldt et al., 2010;
Osipow et al., 1976; Rogers & Westbrook, 1983).
As a result of inconsistent factor structure across previous studies, debates about
application of the different factor analysis, and concerns regarding factors composed
of only two or three items, Osipow (1987) has suggested the use of the total score of
Indecision Subscale as an overall index of career indecision. Hence, most of the
researchers preferred to use Career Indecision Subscale as unidimensional (Betz &
Klein-Voyten, 1997; Constantine, Wallace, & Kindaichi, 2005; Guay, Ratelle,
Senécal, Larose, & Deschênes, 2006; Kinnier, Birgman, & Noble, 1990; Taylor &
Popma, 1990).
In addition, Osipow et al. (1976, 1987) provided the evidence of reliability of the
scale by reporting internal consistency and test-retest reliability. The reported
Cronbach alpha (α) coefficients ranged from .86 to .89 for indecision items and .79
to .90 for certainty items (Sabourin & Coallier, 1991; Savickas & Carden, 1992).
Osipow et al. (1976) obtained two different retest correlations as .90 and .82 for the
73
Indecision Subscale based on two-week interval from two separate sample of
university students (N = 50, N = 59).
3.2.3 Career Decision Self-Efficacy Scale- Short Form (CDSE-SF)
The short form of the Career Decision Self-Efficacy was developed by Betz, Klein
and Taylor (1996) to measure “an individual‟s degree of belief that he or she can
successfully complete tasks necessary to making career decisions” (p. 48). The short
form used in this study consisted of 25 items constructed by eliminating 5 of the 10
items from each of the five subscales from the 50 item version those are self-
appraisal (items 5, 9, 14, 18, 22), occupational information (items 1, 10, 15, 19, 23),
goal selection (items 2, 6, 11, 16, 20), planning (items 3, 7, 12, 21, 24), and problem
solving (items 4, 8, 13, 17, 25). The CDSE-SF reflected five different career choice
competencies developed based on Crites‟s model of career maturity. Items are rated
on a Likert scale ranged as “no confidence at all” (1), “very little confidence” (2),
“moderate confidence” (3), “much confidence” (4), and “complete confidence” (5)
(Betz, Hammond, & Multon, 2005). The possible total scores change between 25 and
125; higher scores on CDSE-SF indicate greater levels of self-efficacy.
The factor structure of the scale was examined by many researchers as an evidence
for the construct validity of the scale. Firstly, Taylor and Betz (1983) performed a
principal components analysis (PCA) with varimax rotation to determine the factor
structure of the 50 items of the CDSE. As a result of PCA, five factors were
74
extracted and accounted for 52% of the total variance. However, items loading on the
factors were not clear. In addition, to evaluate and determine the factor structure of
the short form of the scale, Betz, Klein, and Taylor (1996) conducted PCA with
orthogonal rotation. Accordingly, five factors eigenvalues greater than one that
accounted for 62% of the total variance were found However, distribution of the
items did not confirm the theorized five items in each five factor solution. Hence, as
stated by Betz et al. (1996) five-factor structure was not completely supported in
their study. Various studies produced similar results about the factor structure of the
scale (Peterson & delMas, 1998; Taylor & Popma, 1990). Thus, using the scale as a
generalized measure of career decision-making self-efficacy has been recommended
(Robbins, 1985; Taylor & Popma, 1990).
Betz et al. (1996) reported the internal consistency reliability of the short form
ranged from .73 (Self-appraisal) to .83 (Goal selection) for the subscales and .94 for
the total score. Further, Luzzo (1993) reported a six-week test-retest coefficient of
.83 for the CDSE (50-item version) total score.
3.2.4 Career Outcome Expectations and Exploratory Intentions Scale (OEX-
EI)
Career Outcome Expectations and Exploratory Intentions Scales were developed by
Betz and Klein-Voyten (1997) to assess career decision-making and academic
outcome expectations also exploratory intentions. In general, personal beliefs about
75
probable response termed as outcome expectations which involved the imagined
consequences of performing particular behaviors like that “If I do this, what will
happen?” (Lent et al., 1994, p. 83). Outcome expectations regarding career decision-
making refer to beliefs regarding the long term consequences of success in specific
educational or career decision-making behaviors (Betz & Klein-Voyten, 1997, p.
181). The five-item Academic Outcome Scale (items 1, 2, 3, 4, 5) aimed to assess the
beliefs regarding the relevance of educational performance to future career options
and success. Likewise, outcome expectations regarding career decision-making
behaviors (items 6, 7, 8, 9) were defined as “the belief that those behaviors would be
useful to subsequent career options and decisions” (Betz & Klein-Voyten, 1997, p.
182). The five-item Exploratory Intentions Scale (items 10, 11, 12, 13, 14) assessed
career exploratory plans or intentions which considered as a goal. Five-point Likert
scale used to measure the all responses ranging as “strongly agree” (5), “moderately
agree” (4), “aren‟t sure or neutral” (3), “moderately disagree” (2), and “strongly
disagree” (1).
Coefficient alpha values were reported as .77 (educational outcome), .79 (career
outcome) and .73 (exploratory intentions). “Separate cumulative scores were
calculated for the five educational outcome expectations, the four career decision-
making expectations and the five exploratory intentions” (Betz & Klein-Voyten,
1997, p. 182). Thus, the educational outcome expectations scores changed between 5
and 25, the range of the total score of career decision-making expectations changed
76
between 4 and 20, and the total score of exploratory intentions vary from 5 to 25.
Higher scores indicate high level of expectations or intentions in each scale.
3.2.5 Translation Procedure of the CDS, CDSE-SF, and OEX-EI
The three instruments used in this study, Career Decision Scale (CDS), Career
Decision Self-efficacy Scale Short-Form (CDSE-SF) and Career Decision-Making
Outcome Expectations and Exploratory Intentions Scales (OEX-EI), that were
originally developed in English, translated and adapted into Turkish. Before starting
the translation and adaptation studies, the necessary permissions were obtained from
the publisher (PAR; Psychological Assessment Resources Inc.) of the CDS and
corresponding author (Prof. Dr. Nancy Betz) of the CDMSE-SF and OEX-EI scales
via e-mail.
The steps that were followed throughout the translation process were as follows
(Figure 3.1). First, based on Ægisdóttir, Gerstein, and Canel-ÇınarbaĢ (2008)
suggestion about independent translation of scales by two or more person, the
instruments were given to four experts (two advanced doctoral level counseling
students and two English Language Experts- as one having masters degree in English
Literature and the other in English Language Teaching) independently for translation
into Turkish. Second, the translations made by four experts were compared and best
translation for each item was picked by the researcher and her advisor. Third, the
Turkish versions of the instruments were formed. Fourth, the Turkish and original
77
English versions of the instruments were given to two professors of Psychological
Counseling and Guidance and a professor of Measurement and Evaluation to
evaluate the correctness, clarity, wording of the items, and cultural relevancy of the
Turkish translated versions of the instruments. According to the feedback received
by these three faculty members, some minor changes were made on the Turkish
versions of the CDS, CDSE-SF, and OEX-EI. Forth, three separate focus groups
were conducted to check the understandability, clarity, and cultural appropriateness
of the items of the Turkish versions of the CDS (N = 55) CDSE-SF (N = 55) and
OEX-EI (N = 43) with undergraduate students. Few changes suggested by the
students regarding the wording of the items in three measures were made.
Back translations of the instruments were purposefully avoided as the adequacy of
the translation could be threatened and created both concept and item bias (Van de
Vijver & Hambleton, 1996). However, as a requirement of the Permission
Agreement of the CDS, back-translation of the scale was done.The back-translation
(from Turkish to English) of the CDS was performed by an English language expert
currently working as an instructor at an Academic English Program of a private
university. The expert was unfamiliar with the English version of the CDS. The
back-translation was forwarded to PAR for review. While, back-translation of the
CDS 17 items approved, by PAR, two items (12 and 18) were not and PAR asked for
revision. According to the suggestions of PAR, necessary revisions were made on the
two items. After the revision back-translation of the all items of the CDS has been
approved. Consequently, the Turkish version of the CDS was finalized.
78
Figure. 3.1 Translation and pilot studies of CDS, CDSE-SF and OEX-EI.
Translation of the CDS, CDSE-SF
OEX-EI in to Turkish
Expert opinion for the translated
scales
Student feedback on the scales
Back translation of CDS Turkish version of CDSE-SF
and OEX-EI
Publisher review and approval
Turkish version of CDS
Validity and reliability studies
Final version of the scales
79
3.2.6 Validity and Reliability of the Turkish Version of CDS
In order to test the basic psychometric properties of the scale a pilot study was
carried out with a sample of 336 (112 male, 224 female) undergraduate university
students enrolled in different departments of Middle East Technical University. The
convenience sampling procedure was used in collecting data. The students involved
in the pilot study were not included into the sample of the actual study. The
participants age ranged between 18 and 27, with a mean of 21.25 (SD = 1.60). The
sample of the pilot study was consisted of 109 (32.6 %) freshmen, 85 (25.4 %)
sophomore, 72 (21.6 %) junior, 68 (20.2 %) senior and 2 (.6 %) students did not
report class. The Career Decision Scale was administered in classroom settings by
the researcher.
In order to provide evidence for construct validity of the Career Decision Scale, an
exploratory factor analysis (EFA) was conducted. Prior to factor analysis, the Kaiser-
Meyer- Olkin (KMO) measure of sampling adequacy and Barlett‟s test of sphericity
were examined to determine the appropriateness of the data for factor analysis. The
KMO value was .881 defined as great, thus it is possible to say that the sample size is
adequate for factor analysis (Field, 2009; Hutcheson & Sofroniou, 1999). In addition,
the Barlett‟s test was significant [χ2 (120) = 15552.85, p < .001] indicating large
enough correlations between the items to conduct EFA. As suggested by George and
Mallery (2001) no values lower than recommended .25 was observed in the corrected
total correlation among all the items.
80
In the present study, as in the original study of Osipow et al. (1976), principal axis
factor extraction with varimax rotation was applied to the 16-item Indecision Scale.
Considering the recommendations emphasized using multiple methods (e.g. Coovert
& McNelis, 1988), in the current study, two common factor retention methods were
utilized when deciding on the number of factors: Kaiser‟s criterion (eigenvalues ≥ 1;
Kaiser, 1970) and Cattell‟s scree test (Cattell, 1966). According to Kaiser‟s criterion,
“only the factors that have eigenvalues greater than one are retained for
interpretation” (Ledesma & Valero-Mora, 2007, p. 2). The scree test “involves
examining the graph of the eigenvalues and looking for the natural bend or break
point in the data where the curve flattens out. The number of data points above the
„break‟ (not including the point at which the break occurs) is usually the number of
factors to retain” (Costello & Osborne, 2005, p. 3).
The results of the EFA revealed four factors eigenvalues greater than 1.00 that were
accounted for the 54.7 % of the variance. The first factor accounted for 32.03% of
the total variance (eigenvalue 5.76), the second one 9.40% (eigenvalue 1.69), the
third one 6.99% (eigenvalue 1.25), and the fourth one 6.30% (eigenvalue 1.13).
Factor loadings of the Indecision Subscale items are displayed in Table 3.1 and scree
plot in Figure 3.2. Thus, following the varimax rotation, the first component
explained the %29 of the variance.
81
Figure 3.2 Scree Plot of Indecision Subscale.
82
Table 3.1
Factor Loadings of Indecision Subscale Items
Item number Factor loadings
1 2 3 4
8 .82
9 .53 .33
7 .52 .45
11 .46 .37
10 .46 .34 .36
13 .78
14 .60
18 .56
17 .54
16 .45
15 .39
12 .39
4 .32
3 .64
5 .38 .47
6 .32
Note: Factor loadings < .30 were omitted
In the original study Osipow et al. (1976) presented a four factor structure labeled as
lack of structure and confidence, (items: 5, 7, 8, 9, 10, 11, 13, 14, 17) presence or
perception of some external barriers, (items: 3, 9, 12, 16, 18), approach-approach
(items: 4, 15) and personal conflict (items: 6, 7). Similarly, the results of the factor
analysis of the Turkish version of the Indecision Subscale yielded four factors. The
83
first factor included six items (5, 7, 8, 9, 10, 11), the second four items (7, 10, 13,
14), the third eight items (4, 9, 11, 12, 15, 16, 17, 18) and the forth four items (3, 5,
6, 10). Four items (5, 7, 9, 11) also had double loadings and one item had triple
loadings (10). Thus, the distribution of scale items in the Turkish version of the
indecision was somewhat different from the original study. Specifically, nine items
loaded on the same factors as in original study whereas seven items loaded
differently.
In order to provide evidence for criterion-related validity, Career Decision Scale was
administered with Personal Indecisiveness Scale (PIS; Bacanlı, 2000, 2006b) in a
group of 123 (27 male, 96 female) university students separate from the sample of
the pilot study and the actual study. Correlational analyses indicated a large and
positive correlation (r = .61) between career indecision subscale and total score of
personal indecision as well as a moderate and negative correlation (r = -.34) between
career certainty and personal indecision. It was possible to conclude that these
significant relationships between the two indecision measures were accepted as
evidence for criterion-related validity.
To check the reliability of the scale, the internal consistency and test-retest methods
were used. The internal consistency estimate was measured by means of Cronbach
alpha coefficient (α). The Cronbach alpha values of the Career Decision Scale were
.78 (all items), .86 (Indecision Subscale), and .85 (Certainty Subscale). The test-
retest reliability of the scale was calculated in a sample of 66 university students
84
based on a two-week interval similar to Osipow et al. (1976) study. The correlation
coefficients between these two scale administrations were .81 (for all items), .84 (for
Indecision Subscale), and .77 (for Certainty Subscale). Hence, the test-retest results
were satisfactory and consistent with previous findings (e.g. Osipow et al., 1976).
Moreover, parallel to previous studies, a negative significant association was found
between the Indecision subscale and the Certainty subscale (r = -.50, p < .01).
In the present study taking into consideration the following points a) the previous
inconsistent factor structure results of the Indecision subscale, b) reservations of the
author about using the factor scores (Osipow, 1987), c) relatively high level of
internal consistency of the scale, and d) research problem of the study, Indecision
Subscale was used as unidimensional rather than multidimensional one to assess the
career indecision.
3.2.7 Validity and Reliability of the Turkish Version of CDSE-SF
A pilot study was conducted in a convenience group of 481 (195 male, 286 female)
undergraduate students from different departments and classes at METU to assess the
validity and reliability of the scale. The mean age of the participants was 21.24 and
ranged from 18 to 26 (SD = 1.64). Participants of the pilot study were 126 freshmen,
117 sophomores, 146 juniors, and 92 seniors.
85
After the development of the CDSE (Taylor & Betz, 1983), various factor analytic
studies were conducted by 50-item version and 25-item version of the scale (Betz,
Hammond, & Multon, 2005; Creed, Patton, & Watson, 2002; Hampton, 2005;
Watson, Brand, Stead, & Ellis, 2001). In these studies, several factorial analyses
were employed including the principal component analysis by varimax rotation as
in the original study of Taylor and Betz (1983), principal axis factoring with direct
oblimin rotation (e.g. Creed et al., 2002), confirmatory factor analysis with
maximum likelihood (e.g. Watson et al., 2001). However, most of them did not
confirm the five-factor model of the scale (e.g. Hampton, 2005; Peterson & delMass,
1998).
To check the construct validity and determine the factor structure of the CDSE-SF,
exploratory factor analysis was performed. Prior conducting factor analysis, the
sample size of the pilot study was evaluated by means of KMO and Barlett‟s test of
sphericity. The value of KMO was found .93 and defined as marvelous (Kaiser,
1970). The Barlett‟s test of sphericity was significant [χ2 (300) = 4616.029, p <
.001]. As seen the results of the KMO and Barlett‟s test were satisfactory and
allowed to perform factor analysis. A principal component factor analysis with
varimax rotation was held to determine the factor structure of the scale. The analysis
revealed five factors those eigenvalues higher than one. The five factor solution was
explained the 55.61% of the total variance. The first factor accounted for 35.70%
(eigenvalue 8.92), the second one accounted for 5.40% (eigenvalue 1.35), the third
one accounted for 5.24% (eigenvalue 1.31), the fourth one accounted for 5.16%
86
(eigenvalue 1.29), and the fifth one accounted for 4.08% (eigenvalue 1.02) of the
total variance. Although the five subscales were revealed by principal component
analysis, the distribution of the items was complex and questionable as mentioned by
most of the previous studies (e.g. Peterson & delMas, 1998) because some of the
items had double or triple loadings greater than .30 on more than one factor. In
addition, the scree plot (Figure 3.3) supported a unidimensional model despite of five
factor solution.
Originally, CDSE proposed to have five subscales. The subscales are self-appraisal
(items 5, 9, 14, 18, 22), occupational information (items 1, 10, 15, 19, 23), goal
selection (items 2, 6, 11, 16, 20), planning (items 3, 7, 12, 21, 24), problem solving
(items 4, 8, 13, 17, 25). However, studies including the pioneering work of Taylor
and Betz (1983) did not confirm this theorized five-factor structure of the scale
because the majority items with the loadings of .30 or more loaded on two or more
factors. In the similar vein, the distribution of the CDSE-SF items which factor
loadings were greater than .30 of the Turkish version did not present a five factor
structure. Therefore, the distribution of the items of the Turkish version of the scale
was different from the theorized factor structure (Table 3.2).
Evidence of criterion-related validity of the CDSE-SF was provided by General Self-
efficacy Scale (GSE; Jerusalem & Schwarzer, 1981) in a group of 125 (41 male, 84
female) undergraduate students. Accordingly, the correlation between the GSE scale
and the total CDSE-SF score was .65 (p ≤ .01). Therefore, a significant positive
87
correlation was observed between two different self-efficacy scales in that way
higher levels of career decision making self-efficacy associated with higher level of
general self-efficacy. In addition, Career Decision Scale (CDS; Osipow et al., 1976)
was used to get further evidence from the participants of the actual data (N = 723).
The Pearson product-moment correlation was computed between the CDS Indecision
Subscale and the total score of CDSE-SF scale. The correlation coefficient was found
-.50 (p < .01). Hence there was an inverse relationship between the scales which
means higher level of career decision making self-efficacy associated with lower
level of career indecision. Consequently, it is possible to say that The Turkish
version of the CDSE-SF had sufficient concurrent validity. Factor loadings of the
CDSE-SF items are shown in Table 3.2.
88
Figure 3.3 Scree Plot of Career Decision Self-Efficacy Scale- Short Form.
Moreover, internal consistency reliability and test-retest reliability were used to
evaluate the reliability of the Career Decision Self-Efficacy Scale Short Form. The
internal consistency reliability of the CDSE-SF was .92 for the total score that served
relatively high internal consistency. The item total correlation was ranged from .44 to
.63. A two-week test-retest coefficient of .91 for the total score was computed with
52 undergraduate students separate from the pilot study. The scale served relatively
high reliability when considering the obtained internal consistency and test-retest
coefficients.
89
Table 3.2
Factor Loadings of CDSE-SF Items
Item number Factor loading
1 2 3 4 5
11 .72
9 .70
20 .63 .32
2 .58 .39
16 .57 .36
22 .53 .34 .33
14 .52 .44
7 .74 .33
4 .66
8 .63
5 .48 .58
6 .42 .56
3 .38 .47
10 .35 38 .36
21 .65 .35
15 .61 .31
24 .60
1 .56
12 .36 .53
25 .51 .46
23 .32 .50
17 .78
13 .74
18 .72
19 .40 .60
Note. Factor loadings < .30 were omitted.
90
Taken together, consistent with findings of previous factor analytic studies that failed
to confirm the theorized five-factor structure of the CDSE-SF, which has led to
“consistent recommendations that it only be used as a general measure of decision-
making self-efficacy” Creed et al. (2002, p. 339). Thus, in the present study, total
score of CDSE-SF was used as a generalized measure of career decision-making
self-efficacy as suggested by several authors (Creed et al., 2002; Peterson &
delMass, 1998; Taylor & Betz, 1983; Taylor & Popma, 1990; Watson, Brand, Stead,
& Ellis, 2001).
3.2.8 Validity and Reliability of the Turkish Version of OEX-EI
To assess the validity and reliability characteristics of the Outcome Expectations and
Exploratory Intentions Scale in the Turkish sample a pilot study was performed by a
convenience sample of 303 (115 male, 188 female) undergraduate students from
different classes and departments of METU. The average age of the participants of
the pilot study was 21.17 ranged between 18 and 25 (SD = 1.55). The class of the
students distributed as 26.1% freshmen, 23.8% sophomore, 33.3% junior, and 16.9%
senior in the sample of the pilot study.
To check the construct validity and also factor structure of the Outcome Expectations
and Intentions Scale a principal components factor analyses with oblimin rotation
was used. Before determining the factor structure of the scale, KMO and Barlett‟s
test were examined to decide the appropriateness of factor analysis. The index of
91
KMO was .86 which identified as meritorious (Hair, Anderson, Tatham, & Black,
1998; Kaiser, 1970) and the Barlett‟s test of sphericity was significant [χ2 (91) =
1599.027, p < .001] so the data and sample was suitable to conduct factor analysis.
The principal components analysis yielded three components with eigenvalues
greater than one. The first component explained the %36.03 of the total variance with
an eigenvalue of 5.04, the second component explained the %13.66 with an
eigenvalue of 1.91 and the last component explained the %9.61 with an eigenvalue of
1.34. These three factors accounted for %59.31 of the total variance. The scree test
was supported the three factors solution (Figure 3.4). The factor structure and
distribution of the items were exactly same as the original version of the scale (Betz
& Klein-Voyten, 1997). Hence, the factors named as Academic/ Educational
Outcome Expectations, Career Outcome Expectations and Exploratory Intentions
consistent with the original study of Betz and Klein-Voyten (1997). Only the Career
Outcome Expectations Subscale was used in this study due to the aim of the present
study. Factor loadings are presented in Table 3.3.
92
Figure 3.4 Scree Plot of Outcome Expectations and Exploratory Intentions Scale
93
Table 3.3
Factor Loadings of OEX-EI Scales
Item number Factor Loadings
1 2 3
3 .85
2 .84
5 .73
4 .73
1 .41
11 .83
14 .72
10 .68
12 .67
13 .40
8 .81
7 .74
6 .71
9 .61
Note. Factor loadings < .30 were omitted.
In order to determine the reliability of the scale two widely used methods, Cronbach
alpha and test-retest methods, were preferred. Alpha coefficients, one of the internal
consistency methods, were calculated to check the internal consistency of the scale.
Accordingly, .80 (academic outcome), .81 (career outcome), .82 (total outcome), and
.78 (exploratory intentions) were found. The scale was administered two times in a
group of 58 undergraduate students with a two week interval to examine the test-
94
retest reliability of the scale. The correlations between the administrations were .70
(academic outcome), .76 (career outcome), .83 (total outcome), and .84 (exploratory
intentions). All correlations were significant (p < .001). Thus, it can be claimed that
the scales have sufficient reliability.
3.2.9 Parental Attitude Scale (PAS)
In order to assess the perceived parental attitudes, Parental Attitude Scale was
originally developed by Lamborn et al. (1991) considering the Baumrind‟s (1967 as
cited in Lamborn et al., 1991) framework of parenting styles. The scale composed of
26 items that the first 18 item are scored on a four point Likert type scale, 19th
and
20th
items are scored on seven point Likert type scale, and items between 21 and 26
are scored on a three point Likert type scale. Acceptance/ involvement, strictness/
supervision, and psychological autonomy are the three dimensions of the scale. The
sum of the items 1, 3, 5, 7, 9, 11, 13, 15, and 17 gives the acceptance / involvement
subscale‟s score. Thus, the total score changes between 9 and 36 for the acceptance /
involvement subscale with higher scores indicates higher level of perceived parental
acceptance. The sum of the items 2, 4, 6, 8, 10, 12, 14, 16, and 18 provide the score
of psychological autonomy subscale that total score ranges from 9 to 36. In this
scale, all items are reverse coded except 12. Higher scores accepted as an indicative
of greater perceived parental psychological autonomy. The sum of the items from 19
to 26 offers the score of strictness/ supervision subscale of the PAS. The scoring
95
range of this subscale changes between 8 and 32 with higher scores signify the
higher level of perceived parental strictness/ supervision.
Beyond the three subscales, authoritative, neglectful, authoritarian, and permissive
parenting styles can be obtained by intersection of acceptance/ involvement and
strictness/ supervision dimensions of the scale. However, in the current study, only
the total score of the three subscales were used to assess parental attitudes.
The adaptation studies of The Parental Attitude Scale were performed by Yılmaz
(2000). In the sample of undergraduate students internal reliability and test-retest
reliability coefficients were computed as .79 and .73 for acceptance/ involvement
subscale, .85 and .66 for strictness/ supervision subscale, and .67 and .65 for
psychological autonomy subscale, respectively. Yılmaz (2000) used the academic
achievement to provide the evidence for criterion related validity of the scale. Hence,
the positive significant relationship was found between perceived democratic
attitudes of parents and achievement. Koydemir (2006) was used the scale in a group
of 497 undergraduate students with some minor wording changes like that the
present tense of the items were replaced with past tense. The reliability coefficients
were reported .85 for the total scale; .74 for the acceptance/ involvement subscale;
.82 for the strictness/ supervision subscale; and .65 for psychological autonomy
subscale (Koydemir, 2006). The three factorial structure of the Turkish version of the
scale was confirmed by several authors (Koydemir, 2006; Yılmaz, 2000). It was
assumed that the PAS had sufficient reliability and validity evidence. Therefore, for
96
the present study no further validity study was conducted. The Cronbach alpha
coefficients were found as .70 all items, .68 for acceptance/ involvement; .65 for the
strictness/ supervision; and .78 for psychological autonomy in the current study.
3.2.10 Rotter’s Internal External Locus of Control Scale (IELOC)
Internal- External Locus of Control Scale (IELOC) was originally developed by
Rotter (1966) to assess the generalized expectancies for internal versus external
control of reinforcement. It consisted of 29 forced choice (a / b) items including 6
filler-item (1, 8, 14, 19, 24, 27) that excluded from scoring process. Thus, the
possible scoring range of the scale changed between 0 and 23 with higher scores
accepted as a sign of external locus of control. When scoring, the first choice of the
items 2, 6, 7, 9, 16, 17, 18, 20, 21, 23, 25, and 29 get one point and the second choice
of the following items 3, 4, 5 ,10, 11, 12, 13, 15, 22, 26, and 28 get one point.
The adaptation studies of the IELOC were conducted by Dağ (1991). The test-retest
reliability (23-day) and Cronbach alpha coefficient were reported .83 and .71,
respectively (Dağ, 1991). Satisfactory reliability, construct and criterion-validity
results were presented by Dağ (1991). Thus, the researcher did not conduct any
further validity studies for this widely used scale. For the current study, internal
consistency reliability was found as .71.
97
3.3 Procedure
The data of the pilot studies were collected during 2009-2010 fall semester and the
study data were gathered in 2009-2010 spring semester. Throughout the all data
collection procedures of this study, rules and requirements of the Middle East
Technical University Human Subjects Ethics Committee were followed. All data
were collected in the classroom settings with the permission of the course instructors.
No identifying information were requested from the participants such as name,
surname and student id number to ensure the confidentiality and anonymity of the
subjects. However, in the test-retest applications students‟ id numbers were used to
match the participants between two administrations. The completion of the survey
package that included all measures took approximately 25 minutes.
3.4 Data Analyses
Several steps were followed to analyze the obtained data. Firstly, the data set was
controlled in terms of data entering by using frequencies, minimum and maximum
scores. Then, data cleaning and screening procedure were done to identify missing
values and to check the normality. Secondly, in order to describe the data, descriptive
statistics were used. In addition, Pearson product-moment correlations were
computed to reveal the relationship between the variables. A t-test analysis was
performed to examine the possible gender difference on career indecision. Thirdly,
the presented model was tested by means of Path Analysis via AMOS 18 software
98
program (Arbuckle, 2009). Since each of the variables in the proposed model was
measured by computed scale, the estimated parameters were best interpreted in the
context of a path model. Path analysis preferred rather than regression analysis
because it can help to determine the indirect effects of the variables in the model.
Further, path analysis allows for the decomposition of the effects of variables into
direct, indirect, and total effects (Pedhazur, 1997). A set of additional regression is
added to the original regression analysis to draw out indirect effects. Because of this
complexity, a path diagram is typically used to display all of the causal relationships.
Accordingly, a path analysis separates direct effects and indirect effects thorough a
mediator while regression analysis regards direct effect. In addition, a graphical
language provides a convenient and powerful way to present complex relationships
in path analysis (Ahn, 2002).
3.4.1 Path Analysis
Path analysis is roughly viewed as an extension of the multiple regression models
and a complementary methodology to regression analysis (Ahn, 2002; Garson, 2008;
Schumacker & Lomax, 2004). It is commonly used to “test the likelihood of a causal
connection among three or more variables” (Fraenkel & Wallen, 2006, p. 343). The
aim of path analysis “is to provide estimates of the magnitude and significance of
hypothesized causal connections among sets of variables displayed through the use
of path diagrams which is an illustration wherein the variables are identified and
arrows from variables are drawn to other variables to indicate theoretically based
99
causal relationships” (Stage, Carter, & Nora, 2004, p.5). Mainly, two types of arrows
represented in path diagram which is a schematic representation of models to
indicate connections between variables as “a straight that is one headed arrow
represents a causal relationship between two variables, and a curved two-headed
arrow represents a simple correlation between them” (Loehlin, 2004, p.2). Path
analysis holds strength because it allows researcher to study direct and indirect
effects simultaneously with multiple independent and dependent variables (Stage,
Carter, & Nora, 2004).
In the scope the proposed model of the current study, career indecision, career
decision-making self-efficacy, and career decision-making outcome expectations
were endogenous variables where career decision-making self-efficacy and career
decision-making outcome expectations were mediator; and locus of control and
perceived parental attitudes were exogenous variables. Explanations of the frequently
used terms in path analysis were provided at below.
Path model is defined as a diagram relating independent, intermediary (mediating),
and dependent variables. Single arrows indicate causation between exogenous or
intermediary variables (mediators) and the dependent(s). Double arrows indicate
correlation between pairs of exogenous variables (Garson, 2008; Kline, 2005).
Exogenous variable in a path model is synonymous with independent variable with
no explicit causes (no arrows going to them, other than the measurement error term).
100
Exogenous variables cause fluctuations in the values of other latent variable in the
model. If exogenous variables are correlated, this is indicated by a double-headed
arrow connecting them (Byrne, 2010; Garson, 2008).
Endogenous variable is synonymous with dependent variable and influenced by the
exogenous variables in the model, either directly or indirectly (Byrne, 2010).
Endogenous variables have incoming arrows. Endogenous variables include
mediating causal variables and dependent variables. Mediating endogenous variables
have both incoming and outgoing causal arrows in the path diagram, however, the
dependent variable(s) have only incoming arrows (Garson, 2008).
Mediator refers to a variable that accounts for the relationship between predictor
variable(s) and criterion variable(s) (Baron & Kelly, 1986, p.1176).
Path coefficient / path weight is a standardized regression coefficient (beta) showing
the direct effect of an independent variable on a dependent variable in the path model
(Garson, 2008).
Chi square (χ2) is the most commonly used fit indices to assess how well a model fits
the observed data (Quintana & Maxwell, 1999; Weston & Gore, 2006). A significant
χ2 indicates the model does not fit the sample data. In contrast, a nonsignificant χ
2 is
suggesting that the proposed model is consistent with the observed data. (Weston &
Gore, 2006). Also a nonsignificant χ2
indicates that the covariance matrix and the
101
reproduced model-implied covariance matrix are similar (Schumacker & Lomax,
2004, p.81).
Goodness of fit index (GFI) is a measure of the relative amount of variance and
covariance in sample covariance matrix (S) that is jointly explained by population
covariance matrix (Σ). Values of CFI range from 0 to 1.0, with values close to 1.0
being indicative of good fit (Bryne, 2010).
Adjusted goodness of fit index (AGFI) is the adjusted GFI for the number of degrees
of freedom in the specified model. Similar to GFI, the values of AGFI range from 0
to 1.0, with values close to 1.0 being indicative of good fit (Bryne, 2010).
Comparative fit index (CFI) is an example of an incremental fit index which
compares the improvement of the fit of the researcher‟s model over a more restricted
model, called an independence or null model, which specifies no relationship among
variables. CFI ranges from 0 to 1.0, with values closer to 1.0 representing better fit
(Weston & Gore, 2006, p. 742).
Root mean square error of approximation (RMSEA) is an index that corrects for a
model‟s complexity. When two models explain the observed data equally well, the
simpler model will have the more favorable RMSEA value (Weston & Gore, 2006).
Interpretations of RMSEA value has been suggested as the following: 0 = an exact
102
fit, < .05= a close fit, .05 to .08 = a fair fit, .08 to .10 = a mediocre fit, and .10 > = a
poor fit (MacCallum, Browne, & Sugawara, 1996).
Standardized RMR based on covariance residuals. It is a summary of how much
difference exists between the observed data and the model (Weston & Gore, 2006). It
ranges from 0 to 1.00; in a well fitting model, this value will be small which means
.05 or less (Bryne, 2010).
3.5 Limitations of the Study
This study has some limitations that should be undertaken when evaluating the
results of the study and its contributions. Since self-report instruments were used to
gather data, the participants may have responded to the instruments to obtain social
desirability even if they were ensured confidentiality and anonymity. Thus, the
accuracy of the results limited with the sincere answers of the participants.
Secondly, even if the sample size was relatively large enough to carry out the study
and to obtain a representative sample at least five percent of all faculties and classes
were considered, the sampling procedure did not rely on random sampling which
limits the generalizability of the findings.
103
Thirdly, the current study was carried out with university students from only one
state university (METU) in Turkey that limits the generalizability of the findings to
other university students from different regions of Turkey.
Lastly, in the present study, predictors of career indecision are limited the included
variables which were locus of control, perceived parental attitudes, career decision-
making self-efficacy, and career decision-making outcome expectations that
explained 32% of the career indecision.
104
CHAPTER IV
RESULTS
This chapter presents the results of the study. It starts with preliminary analyses
together with missing data and outlier analyses, assumptions, and demographic
variables. Then, results regarding descriptive statistics and correlations among
variables were provided. Afterward, path analyses for testing the proposed model and
trimmed model as well as direct and indirect relations and hypotheses testing were
presented.
4.1 Preliminary Analyses
Prior to analyzing the data, variables of the study were checked in terms of missing
values, univariate and multivariate outliers, and the assumptions including
independence of observations, sample size, normality, linearity, homoscedasticity
and multicollinearity through SPSS-PAWS 18 Program.
4.1.1 Missing Data and Outlier Analyses
Missing value analysis was performed to detect missing values in the data set.
Tabachnick and Fidell (2007) stated that missing values that exceeds 5% is a
significant problem. Accordingly, 8 cases with missing values more than 5% were
deleted as suggested by Tabachnick and Fidell. Subsequently, to maximize the
105
sample size, cases with missing values fewer than 5 % were replaced by the variable
mean.
To determine the univariate outliers for each variable, standardized scores (z scores)
were used. Cases with z scores exceed ± 3.29 range viewed as potential outliers
(Tabachnick & Fidell, 2007). However, Hair, Anderson, Tatham, and Black (1998)
stated that “when the sample sizes are larger, the guidelines suggest that the
threshold value of standard scores range from 3 to 4” (p. 65). According to Hair et
al., (1998) no cases fall outside of the range, hence, no univariate outliers identified
in the data set. In addition, Mahalanobis distance value was computed to determine
multivariate outliers. Subsequently, 11 cases exceed the chi-square criterion of 22.46
(df = 6, p < .001) were identified as multivariate outliers and were excluded from the
data set.
4.1.2 Assumptions of the Path Analysis
Before conducting any statistical analysis a number of assumptions such as
independence of observations, sample size, normality, linearity, homoscedasticity
and multicollinearity were checked.
Even if the data were collected in the classroom settings, the researcher did not
allow any interaction among participants to ensure that all observations were
independent.
106
There are several guidelines regarding the adequate sample size for example, Stevens
(2002, p. 143) suggested “15 subjects per predictor”. Tabachnick and Fidell (2007, p.
123) provided a formula (N > 50 + 8m; m = number of independent variables) to
determine required sample size. According to Kline (2005), sample size should be at
least 200 to conduct path analysis. Consequently, the sample size of the study (N =
723) was large enough to perform path analysis.
The data were also examined for univariate and multivariate normality with
skewness and kurtosis. Thus, to assess the univariate normality, skewness and
kurtosis values for each study variables were examined. As can be seen values for the
skewness and kurtosis statistics presented in Table 4.1 were within the acceptable
range of ± 3 (Field, 2009; Stevens, 2002; Tabacknick & Fidell, 2007). In addition to
univariate normality, multivariate normality was assessed with scatterplots of all
variables in relation to one another. When variable combinations are normal,
scatterplots display elliptical shapes (Mertler & Vannatta, 2010). Accordingly,
scatterplot matrix demonstrated relatively elliptical shapes for all combinations of the
study variables which indicate multivariate normality (Figure 4.1).
107
Table 4.1
Indices of Normality for Study Variables
Variable Skewness Kurtosis
Career Indecision .21 -.86
CDMSE -.10 -.04
CDMOEX -.79 .71
Locus of Control -.26 -.33
Parental Attitudes
Acceptance/ Involvement -.67 .59
Strictness/ Supervision .17 -.82
Psychological Autonomy -.41 -.30
Note. CDMSE = Career decision-making self-efficacy; CDMOEX = Career decision-
making outcome expectations.
108
COEXT
CDSET
Autonomy
Supervision
Acceptance
LOC
Indecision
Indecision
Acceptance
Autonomy
COEXT
Figure 4.1 Scatterplot matrix of all study variables.
109
Regression Standardized Predicted Value
420-2-4
Regression Standardized Residual
3
2
1
0
-1
-2
-3
Scatterplot
Dependent Variable: Indecision
Beyond the scatterplots, residual plot was used to examine the assumptions of
normality, linearity, and homoscedasticity. In the current study, residuals displayed
an approximate rectangular distribution with scores concentrated in the center
(Figure 4.2).
Figure 4.2 Scatterplot of standardized predicted values by standardized residuals.
To sum up, it is possible to conclude that the assumptions of normality, linearity, and
homoscedasticity among the variables included in the model were met. As a result of
preliminary analyses, of the 742 participants, responses from 19 participants were
excluded from the data set. Thus, the final sample of the study consisted of 723
participants for further analyses.
110
4.2 Demographic Analyses
In the present study, the inclusion of demographic variables to the model did not
yield any significant results. Therefore, separate analysis such as independent
samples t tests, one-way analysis of variances (ANOVAs) and Pearson Product
Moment correlations were computed to understand whether career indecision level of
the participants differed with respect to demographic variables of gender, grade,
faculty, age and also the academic achievement.
Firstly, an independent samples t-test was employed to determine the possible gender
difference on career indecision. Accordingly, results of the analyses revealed that
there was no significant differences between female and male students career
indecision [t (719) = -.42, p = .67] scores.
A between-groups ANOVA was employed to explore the influence of class on career
indecision. Results revealed significant differences [F (3, 717) = 6.23, p = .00]
indicating that career indecision level of participants differed significantly according
to their class. Post-hoc comparison (Tukey HSD) indicated that the mean of
freshmen students (M = 33.16, SD = 8.45) was significantly different from senior
students (M = 29.38, SD = 8.98). Thus, freshmen experienced more career indecision
than seniors.
111
To examine if the level of career indecision differed according to faculty, another
between-groups ANOVA was conducted. There are mean differences among
faculties with respect to career indecision. Accordingly, Faculty of Education (M =
30.84, SD = 9.15) and Faculty of Engineering (M = 30.96, SD = 8.57) had the lowest
mean career indecision scores. In contrast, Faculty of Economic and Administrative
(M = 32.64, SD = 8.98), Faculty of Architecture (M = 32.40, SD = 7.97), and Faculty
of Arts and Sciences (M = 31.13, SD = 7.96) had the highest mean career indecision
scores, respectively. However, these observed mean differences were not significant
[F (4, 715) = 1.29, p > .05].
Furthermore, in order to investigate the relationships among age, academic
achievement, and career indecision, Pearson product-moment correlation coefficients
were used. Both age and academic achievement were negatively correlated with
career indecision (r = -.8, p < .05, r = -.13, p < .01, respectively). In other words,
older and successful students reported lower level of career indecision.
4.3 Descriptive Statistics and Correlations
Descriptive statistics, including means and standard deviations, were computed for
each variable in the sample (Table 4.2). In the present study, the mean of career
indecision score for the total sample was 31.43 (SD = 8.68). This mean value is
similar to values reported in previous studies conducted with university students.
Tokar et al. (2003) gathered data from 350 university students and reported the mean
112
for total indecision as 29.76 (SD = 10.22). In another study, Kang (2009) reported the
mean of career indecision as 32.17 (SD = 9.02) for total sample and identified this
value as high level of career indecision.
The current sample‟s mean on the CDSE-SF was compared to available means
obtained from university students. Betz et al. (2005), for example, reported the mean
of the total score for the CDSE-SF as 95 (SD = 16.25; N = 1399). Duffy and Lent
(2008) reported a total mean score of 102.7 (SD = 15.22; N = 133) for the CDSE-SF.
In another study conducted with 220 African American university students, Chaney,
Hammond, Betz, and Multon, (2007) reported a total mean score of 100 (SD = 17)
for the CDSE-SF. In the current investigation, the mean of the CDSE-SF for the total
score was found to be 87.39 (SD = 14.63) that was slightly lower than previously
reported means, indicating that participants involved in the current study obviously
had less career decision making self-efficacy than the samples of previous studies.
In the current study, mean of the Career Outcome Expectations Subscale was
compared to original study of Betz and Klein-Voyten (1997). In their study with 345
university students, the mean of the career outcome expectations was reported as
17.6 (SD = 2.2) for females and 17.5 (SD = 2.7) for males. In the present sample, the
observed mean for career outcome expectations was found to be 15.68 (SD = 2.82),
15.74 (SD = 2.94), and 15.60 (SD = 2.70) for entire sample, females and males
respectively. Hence, the means were somewhat lower than reported means of the
113
original study, indicating that the participants of the present study had less career
outcome expectations.
Mean of the Rotter‟s IE Locus of Control Scale attained by the present study was
compared to Rotter‟s (1966) normative data. The mean for the normative data on the
Rotter IE Scale was 8.29 with a standard deviation of 3.97 (N = 1180). The mean for
the IE Scale in this study‟s sample (M = 11.92, SD = 4.07) was quite different from
Rotter‟s normative data. Hence, participants of the current study seemed more
externally controlled.
In the current study, means on the acceptance/ involvement, strictness/ supervision,
and psychological autonomy subscales of the Parental Attitudes Scale were
compared to available means obtained from university students. For example,
Koydemir (2006) carried out a study with university students (N = 497) and found
the means to be 17.12 (SD = 4.65), 17.52 (SD = 2.85), 24.41 (SD = 4.33) for the
acceptance/ involvement, strictness/ supervision, and psychological autonomy
subscales respectively. In the current study, however, obtained means (MAcceptance =
27.59, SD = 4.05; MStrictness = 21.73, SD = 5.42; MAutonomy = 26.89; SD = 5.01) were
higher than previous reported means, suggesting that the participants of the current
study apparently experienced greater acceptance/ involvement, strictness/
supervision, and psychological autonomy from their parents than the sample of
previous study.
114
Tab
le 4
.2
Mea
ns,
Sta
ndar
d D
evia
tions
and I
nte
rcorr
elat
ions
7 -
Note
. N
= 7
23. C
I =
Car
eer
Indec
isio
n;
CD
MS
E =
Car
eer
dec
isio
n-m
akin
g s
elf-
effi
cacy
; C
DM
OE
X =
Car
eer
dec
isio
n-
mak
ing o
utc
om
e ex
pec
tati
ons;
LO
C =
Locu
s of
Contr
ol;
A/I
= A
ccep
tance
/ In
volv
emen
t; S
/S =
Str
ictn
ess/
Super
vis
ion;
P/A
= P
sych
olo
gic
al A
uto
nom
y.
**p <
.01, tw
o-t
aile
d;
*p <
.05, tw
o-t
aile
d.
6 -
-.14**
5 -
.18**
.23**
4 -
-.11**
.11**
-.08*
3 -
-.05
.19**
.06
.09*
2 -
.26**
-.22**
.25**
-.06
.17**
1 -
-.50**
-.01
.19**
-.15**
.03
-.30**
SD
8.6
8
14.6
3
2.8
2
4.0
7
4.0
5
5.4
2
5.0
1
M
31.4
3
87.3
9
15.6
9
11.9
2
27.5
9
21.7
3
26.8
9
Var
iable
1.C
I
2.C
DM
SE
3.C
DM
OE
X
4.L
OC
5.A
/ I
6. S
/ S
7. P
/ A
115
Further, bivariate correlations among all of the variables were computed to
understand the relationships among the study variables and to detect the assumptions
of multicollinearity. Therefore, Pearson product-moment correlation coefficients
were calculated to evaluate the relationships among exogenous variables of locus of
control, parental acceptance/ involvement; parental strictness/ supervision, and
parental psychological autonomy; mediator variables of career decision-making self-
efficacy and career decision-making outcome expectations; and endogenous variable
of career indecision. The correlation matrix for the entire sample is shown in Table
4.2.
In addition, the correlations among the variables of the study were controlled to
check the multicollinearity and no highly correlated (.7 or more) variables were
observed (Tabachnick & Fidell, 2007).
Overall examination of the correlations among the variables for the entire sample
indicated no significant correlations at the .001 level. However, many significant
relationships can be seen at the .01 and .05 levels (Table 4.2). The significant
correlation coefficients were changed in a range of .08 to .50.
As expected, career indecision was largely negatively correlated with career
decision-making self-efficacy (r = -.50, p < .01). A moderate positive correlation was
found between career indecision and locus of control (r = .19, p < .01). Among
dimensions of perceived parental attitudes, parental acceptance/ involvement and
116
parental psychological autonomy were negatively correlated with career indecision (r
= -.15, p < .01; r = -.30, p < .01, respectively). No significant relationship was
revealed between strictness/ supervision dimension of perceived parental attitudes
and career indecision (r = .03, p > .05).
Consisted with the anticipated relationships, while career decision-making self-
efficacy, acceptance/ involvement, and psychological autonomy dimensions of
parental attitudes were negatively related to career indecision; locus of control was
positively associated with career indecision. However, no significant association was
found between career decision-making outcome expectations and career indecision (r
= -.01, p > .05).
117
4.4 Path Analysis: Testing the Proposed Career Indecision Model
In order to test the strength of independent variables in influencing the outcome
variable and the potential mediating role of career decision-making self-efficacy and
career decision-making outcome expectations, two separate path analyses were
carried out by AMOS 18 program (Arbuckle, 2009). Path analysis allows
investigating the path model by evaluating both direct and indirect relations between
variables (Byrne, 2010).
As the proposed model intends, whether the model accounted for the direct relations
of locus of control, career decision-making self-efficacy, and career decision-making
outcome expectations with career indecision; the direct relations of locus of control,
parental acceptance/ involvement, parental strictness/ supervision, and parental
psychological autonomy with both career decision-making self-efficacy and career
decision-making outcome expectations; the direct relation of career decision-making
self-efficacy with career decision-making outcome expectations; the indirect
relations of locus of control, parental acceptance/ involvement, parental strictness/
supervision, and parental psychological autonomy with career decision-making
outcome expectations; and the indirect relations of locus of control, parental
acceptance/ involvement, parental strictness/ supervision, and parental psychological
autonomy, and career decision-making self-efficacy with career indecision were
tested.
118
The first path analysis was employed to test the proposed path model as depicted in
Figure 1.2 (p. 11) which including career decision-making self-efficacy and career
decision-making outcome expectations as mediators between exogenous variables
(locus of control, perceived parental acceptance/ involvement, perceived parental
strictness/ supervision, and perceived parental psychological autonomy) and career
indecision to understand how well the data fitted the proposed model. Amos 18
(Arbuckle, 2009) with maximum likelihood estimation (MLE) was used to conduct
path analysis and to compute path coefficients as well as model fit indices.
To evaluate model fit, chi-square value ( and significance, the ratio of chi-square
to its degrees of freedom ( , the goodness of fit index (GFI), the comparative
fit index (CFI), the Tucker-Lewis index (TLI), normed fit index (NFI) and the root-
mean-square error of approximation (RMSEA) were used goodness of fit indices.
The recommended cutoff values for each goodness of fit index summarized in Table
4.3.
Table 4.3
Acceptable Cutoff Values for Goodness of Fit Indices
Note. a. Kline (2005); b. Bentler and Bonett (1980); c. Bentler (1990);
d. Hu and Bentler (1999); e. Schumacker and Lomax (2004).
Goodness of Fit Indices
df GFI CFI TLI NFI RMSEA
Optimal Value - - < 3.0a
> .95e
> .95c
> .95d
> .90b < .06
d
119
In the current study, the first path analysis that evaluated the proposed model
revealed large and statistically significant chi-square statistic value (3, N = 723) =
48.31, p = .00. Whereas a nonsignificant chi-square suggests good model-to-data fit,
a significant chi-square suggests a poor model to data fit. In addition, the ratio of
to degrees of freedom (df) was calculated. However, the value of this ratio / df =
48.31 / 3 = 16.1 was far away from recommended value of 3 (Kline, 2005).
Chi-square is sensitive to sample size. With large sample size, the chi-square yields
significant values (Schumacker & Lomax, 2004). In order to deal with limitations of
chi-square statistics, other various goodness of fit indices (e.g., the goodness of fit
index; GFI, the comparative fit index; CFI, and the root-mean-square error of
approximation; RMSEA) are recommended to assess model fit.
Obtained goodness of fit indices for the first path analysis is presented in Table 4.4.
According to these indices, fit statistics for the proposed model indicated less than
adequate fit.
Table 4.4
Summary of Model-Fit Statistics for the Proposed Model
Goodness of Fit Indices
df GFI CFI TLI NFI RMSEA
Proposed Model 48.3 3 16.1 (> 3)
.98 .91
.39
.91 .15
120
Even though some of the fit indices as GFI = .98, CFI = .91, NFI = .91 seemed to be
acceptable, the chi-square statistics (p < .05), TLI (.39), and the RMSEA values (.15)
suggested poor model fit with the data. An examination of the path coefficients
among the variables revealed four nonsignificant paths (represented by the dashed
lines in Figure 4.3). Considering the result of the first path analysis, the model was
trimmed and tested via second path analysis.
121
Str
ictn
ess/
Su
per
vis
ion
.08
*
-.1
6**
*
.20
***
.2
2**
*
.12
***
-.5
0**
*
.10
**
**
.11
***
Locu
s of
Con
trol
Acc
epta
nce/
Involv
emen
t
Psy
cholo
gic
al
Au
ton
om
y
Care
er
Ou
tcom
e
Exp
ecta
tion
s
Care
er
Deci
sion
-mak
ing
Sel
f-ef
fica
cy
Care
er
Ind
ecis
ion
Fig
ure
4.3
Sta
ndar
diz
ed P
ath C
oef
fici
ents
for
the
Pro
pose
d M
odel
*p <
.05;
**
p <
.01;
***
p <
.001.
122
4.5 Path Analysis: Testing the Trimmed Career Indecision Model
Because the overall model was a poor fit of the data, the model was trimmed to reach
a more parsimonious model by eliminating of existing four nonsignificant paths and
by adding a new path suggested by modification index. Specifically, the following
paths were nonsignificant: the path between perceived parental strictness/
supervision and career decision-making self-efficacy; the path between perceived
parental strictness/ supervision and career decision-making outcome expectations;
the path between perceived parental psychological autonomy and career decision-
making outcome expectations, and the path between locus of control and career
decision-making outcome expectations. As a result of these nonsignificant paths,
supervision/ strictness one of the perceived parental attitudes was excluded from the
model because it was remained unrelated to both mediator variables and dependent
variable. Moreover, a direct path was recommended from perceived parental
psychological autonomy to career indecision. The modification index for this path is
43.70 and expected parameter change is .364.
Subsequently, recommended changes were made to improve the fit of the model and
a path analysis was rerun with the trimmed model. Standardized path coefficients for
the paths of the trimmed model are presented in Figure 4.4. An examination of the
path coefficients among the variables of the trimmed model indicated that all of the
paths including the correlations among exogenous variables (locus of control and
perceived parental attitudes) were significant.
123
The same model-fit statistics, namely chi-square ( ), the ratio of chi-square to its
degrees of freedom / df), the goodness of fit index (GFI), the comparative fit
index (CFI), the Tucker-Lewis index (TLI), normed fit index (NFI), and the root-
mean-square error of approximation (RMSEA) were computed for the trimmed
model.
In the trimmed model, (3, N = 723) = .382, p = .94, signifying that the model was
a good fit of the data. Moreover, fit indices for the trimmed model indicated a good
model to data fit: GFI = 1.00, CFI = 1.00, and TLI = 1.00. The summary of model-fit
statistics for the trimmed model is displayed in Table 4.5. As a result of the second
path analysis which did not reveal any nonsignificant path and did not suggest any
further modification, the trimmed model was accepted as the final path model of
career indecision. Thus, the trimmed model fits the data significantly better than the
proposed model.
Table 4.5
Summary of Model-Fit Statistics for the Trimmed Model
Goodness of Fit Indices
df GFI CFI TLI NFI RMSEA
Trimmed Model 382 3 .13 (< 3)
1.00 1.00
1.00
1.00 .00
124
Regarding the research question, the squared multiple correlation coefficient (R2)
indicated that the trimmed model accounted for 32% of the variance in career
indecision. Concerning the mediators, in the trimmed model accounted for 11% of
the variance in career decision-making self-efficacy, and 8% of the variance in career
decision-making outcome expectations.
125
.0
7*
-.1
9**
*
.20
***
.2
2**
*
.14
***
-.4
8**
*
.11
**
.14
***
-.2
2*
**
Locu
s of
Con
trol
Acc
epta
nce/
Involv
emen
t
Psy
cholo
gic
al
Au
ton
om
y
Care
er
Ou
tcom
e
Exp
ecta
tion
s
Care
er
Deci
sion
-mak
ing
Sel
f-ef
fica
cy
Fig
ure
4.4
Sta
ndar
diz
ed P
ath C
oef
fici
ents
for
the
Tri
mm
ed M
odel
*p <
.05;
**
p <
.01;
***
p <
.001.
Care
er
Ind
ecis
ion
126
4.5.1 Direct and Indirect Relationships
As shown in Figure 4.4, the path coefficients varied from .07 to -.48 for trimmed
model. Cohen (1992) proposed effect size index and their values for standardized
path coefficient (β) as values less than .10 indicate a "small" effect; values around .30
a "medium" effect; and values of .50 or more a “large" effect. Accordingly, career
decision-making self-efficacy (β = -.48) had the largest direct effect on career
indecision. Conversely, locus of control (β = .07) had the lowest direct effect on
career indecision. Among the nine paths, three of them are negative (Figure 4.4).
The standardized direct and indirect effects and their statistical significance for the
trimmed model were calculated and summarized in Table 4.6. The indirect effects
specified in hypotheses were estimated via bootstrapping (set at 1000), and bias
corrected bootstrap (BC) 95% confidence intervals were requested. Bootstrapping is
being used with increasing frequency and recommends by many researcher (Preacher
& Hayes, 2008; Williams & MacKinnon, 2008). It is basically a statistical method of
resampling from the original data set that provides significance of indirect effects
(Kline, 2005). Further, the standardized total, direct, indirect (total), and specific
indirect effects and their statistical significance for the trimmed model were
calculated and summarized in Table 4.6. The specific indirect effects was calculated
using Preacher and Hayes‟ (2008) macro for multiple mediator models because
AMOS provides BC bootstrap confidence intervals for the total indirect effect but
not for the specific indirect effects.
127
Table 4.6
Standardized Total, Direct, and Indirect Estimates of the Trimmed Model
Paths Standardized Estimates
(β)
LOC Career Indecision
Total .16***
Direct .07*
Indirect (total) .09**
Acceptance Career Indecision
Total -.07**
Direct -
Indirect (total) -.07**
Indirect by CDMSE -.10**
Indirect by CDMOEX .03**
Autonomy Career Indecision
Total -.27***
Direct -.22***
Indirect (total) -.05**
CDMSE Career Indecision
Total -.45***
Direct -.48***
Indirect (total) .03**
CDMOEX Career Indecision
Total .14***
Direct .14***
Indirect (total) -
Note. CI= career indecision; CDMOEX = career decision-making outcome
expectations; CDMSE = career decision-making self-efficacy; LOC = locus of
control; Autonomy = perceived parental psychological autonomy; Acceptance =
perceived parental acceptance/ involvement.
*p < .05; **p < .01; ***p < .001.
128
4.5.2 Hypotheses Testing
Hypothesis 1: There will be a relation between locus of control and career
indecision. The results supported the Hypothesis 1 that there was a significant and
positive relationship (β = .07, p < .05) between locus of control and career
indecision.
Hypothesis 2a: Locus of control will be related to career indecision indirectly
through career decision-making self-efficacy. The results confirmed the Hypothesis
2a that locus of control was related to career indecision indirectly through career
decision-making self-efficacy (β = .09, p < .01).
Hypothesis 2b: Locus of control will be related to career indecision indirectly
through career decision-making outcome expectations. The results of the study
indicated that locus of control was not related to career indecision indirectly through
career decision-making outcome expectations (β = .00, p > .05).
Hypothesis 3a: Perceived parental acceptance/ involvement will be related to career
indecision indirectly through career decision-making self-efficacy. Hypothesis 3a
was accepted as perceived parental acceptance/ involvement was associated with
career indecision indirectly through career decision-making self-efficacy (β = -.10, p
< .01).
129
Hypothesis 3b: Perceived parental acceptance/ involvement will be related to career
indecision indirectly through career decision-making outcome expectations. The
results verified the hypothesis 3b as perceived parental acceptance/ involvement was
related to career indecision indirectly (β = .03, p < .01) through career decision-
making outcome expectations.
Hypothesis 4a: Perceived parental strictness/ supervision will be related to career
indecision indirectly through career decision-making self-efficacy. Hypothesis 4a
was rejected because perceived parental strictness/ supervision was excluded from
the trimmed model.
Hypothesis 4b: Perceived parental strictness/ supervision will be related to career
indecision indirectly through career decision-making outcome expectations. As in
Hypothesis 4a, Hypothesis 4b was rejected because perceived parental strictness/
supervision was excluded from the trimmed model.
Hypothesis 5a: Perceived parental psychological autonomy will be related to career
indecision indirectly through career decision-making self-efficacy. The results of the
study supported the hypothesis as in perceived parental psychological autonomy was
related to career indecision indirectly (β = -.05, p < .01) through career decision-
making self-efficacy.
130
Hypothesis 5b: Perceived parental psychological autonomy will be related to career
indecision indirectly through career decision-making outcome expectations. The
hypothesis was rejected because perceived parental psychological autonomy was not
related to career indecision indirectly (β = .00, p > .05) through career decision-
making outcome expectations. Beyond the hypotheses 5a and 5b, as a result of the
first path analysis a direct path suggested by modification index was added from
perceived parental psychological autonomy to career indecision (β = -.22, p < .001).
Hypothesis 6: There will be a relation between career decision-making self-efficacy
and career indecision. Hypothesis 6 was accepted as there was a significant direct
relationship between career decision-making self-efficacy and career indecision (β =
-.48, p < .001).
Hypothesis 7: Career decision-making self-efficacy will be related to career
indecision indirectly through career decision-making outcome expectations. The
hypothesis was confirmed by the results. Accordingly, career decision-making self-
efficacy was associated with career indecision indirectly (β = .03, p < .01) through
career decision-making outcome expectations.
Hypothesis 8: There will be a relation between career decision-making outcome
expectations and career indecision. The hypothesis was accepted as there was a
significant direct relationship between career decision-making outcome expectations
and career indecision (β = .14, p < .001).
131
Overall, the results of the path analysis revealed that the all variables except
perceived parental strictness/ supervision included in the model were significantly
related to career indecision of students. Most of the stated hypotheses were
confirmed by the results of the study. More specifically, as hypothesized locus of
control and career decision-making self-efficacy were related to career indecision
both directly and indirectly. Perceived parental attitudes influenced career indecision
indirectly whereas career outcome expectations influenced career indecision directly.
Considering the values obtained from the multiple fit indices along with statistically
significant parameters, the trimmed model of career indecision was supported by the
data.
132
CHAPTER V
DISCUSSION
This chapter presents a general discussion along with discussions of hypothesized
relationships between studied variables based on the findings obtained from the
current study that is followed by implications and recomendations for research and
practice.
5.1 General Discussion
The purpose of the current investigation was to examine the predictors of career
indecision with in a proposed model based on social cognitive career theory (Lent et
al., 1994). In particular, this study investigated the role of locus of control, perceived
parental attitudes (acceptance/ involvement, psychological autonomy, strictness/
supervision), career decision-making self-efficacy, and career outcome expectations
and how they interact to influence career indecision among Turkish university
students. Accordingly, a mediational model was proposed and tested in which locus
of control and perceived parental attitudes were proposed to interact with career
decision making self-efficacy and career outcome expectations to predict career
indecision. Path analysis was utilized to test the proposed career indecision model
illustrated in the Figure 1.2 (p. 11). Career development and choice literature have
identified multiple factors that contribute to career indecision of university students.
133
Even if there are many studies carried out with university students to test the social
cognitive career theory, no research has been found to examine the multiple
associations among these variables utilized SCCT in Turkey.
Demographic influences on career indecision investigated along with various intra-
personal, interpersonal, and environmental variables. Gender, age, class, and
academic achievement were more frequently examined demographics. Results of the
present study revealed no significant difference between the female and male
students‟ career indecision scores. Although the present study conducted in a
different cultural context from previous studies, the obtained finding concerning the
gender difference was consistent with most of previous studies (Browne, 2005;
Creed, Patton, & Prideaux, 2006; Guerra & Braungart-Rieker, 1999; Kang, 2009;
Osipow, Carney, & Barak, 1976; Taylor, 1982, Weiss, 2000). Accordingly, the
proposed model tested for the entire sample.
In the present study, as in previous studies (Ng & Feldman, 2009; Peng & Herr,
2002; Rohner et al., 2009) results yielded a significant negative relationship between
age and career indecision suggesting that younger students experience more career
indecision than older students. With regard to class, significant difference between
freshmen and seniors career indecision scores was found. This finding is in line with
previous studies in which freshmen reported more career indecision than seniors
(Guerra & Braungart-Rieker, 1999; Peng & Herr, 2002).
134
Results of this study concerning the relation between academic achievement and
career indecision produced a negative correlation. In the literature, there is no clear
agreement about the direction of the relationship between academic achievement and
career indecision. While some studies indicate negative relationship (e.g. Osipow
&Waddell, 1980; Daggit 1996), some others (e.g, Abu Talib & Kit Aun, 2009),
report a positive correlation between age and career indecision. Furthermore results
did not provide any significant differences between the career indecision scores of
students enrolled in different faculties.
The current study proposed a model in which there were multiple predictors and
mediators of career indecision. Path analysis was used to test this proposed model.
The results of the path analysis were somewhat mixed and yielded that proposed
model was not supported by the data. As a result of path analysis, to improve the
model some modifications were recommended. Accordingly, some nonsignificant
relationships were excluded from the model and a significant path was added to the
model. Then, the path analysis was rerun to test the trimmed model. Results of the
analysis for trimmed model provided a perfect fit to the data and it was theorethically
sound.
5.2 Hypothesized Relationships between Locus of Control and Career
Indecision
Findings of the current study supported the first hypothesis that locus of control
would be directly related to career indecision illustrated by Path 1 depicted in the
Figure 4.4 (see p. 125). Thus results suggested that external locus of control seems to
135
be associated with greater career indecision. This finding was similar to prior studies
(Simon, 1990; Saunders, 1997; Taylor, 1982) that showed significant and positive
relationship between locus of control and career indecision.
Secondly, it was hypothesized that locus of control would be related to career
indecision indirectly through career decision-making self-efficacy (Hypothesis 2a;
Path 2 and Path 11) and locus of control would be related to career indecision
indirectly through career outcome expectations (Hypothesis 2b; Path 3 and Path 12).
Results confirmed the hypothesis 2a that locus of control was related to career
indecision indirectly through career decision making self-efficacy. Accordingly,
proposed individual paths between locus of control to career decision making self-
efficacy (Path 2) and between career decision making self-efficacy and career
indecision (Path 11) were significant. Similar to Taylor and Popma (1990), locus of
control was found to be moderately and negatively related to career decision-making
self-efficacy and career indecision; suggesting that participants who were more
externally controlled had lower career decision-making self-efficacy and had greater
career indecision. Career decision-making self-efficacy was found to be negatively
and largely related to career indecision. However, the results of the study did not
verify the hypothesis 2b; locus of control did not related to career indecision
indirectly through career outcome expectations.
In conclusion, consistent with previous findings (e.g. Woodbury, 1997; Taylor, 1982)
the findings of the present study indicated that locus of control is seen as a significant
136
predictor of career indecision. In addition, the findings of the current study provided
further evidence for SCCT (Lent et al., 1994) as career decision-making self-efficacy
was a significant mediator for the relation between locus of control and career
indecision.
5.3 Hypothesized Relationships between Perceived Parental Attitudes and
Career Indecision
Six separate hypotheses regarding the association between perceived parental
attitudes and career indecision were stated. It was hypothesized that perceived
parental acceptance/ involvement would be indirectly related to career indecision
through career decision-making self-efficacy (Hypothesis 3a; Path 4 and Path 11).
Hypothesis 3a was supported by the results indicating that there was a moderate and
negative indirect relationship between perceived parental acceptance/ involvement
and career indecision through career decision-making self-efficacy. Proposed
individual paths between perceived parental acceptance/ involvement and career
decision-making self-efficacy (Path 4) and between career decision-making self-
efficacy and career indecision (Path 11) were significant. Thus, perceived parental
acceptance/ involvement was positively related to career decision-making self-
efficacy, which in turn, was negatively related to career indecision; participants who
had more perceived parental acceptance/ involvement had more career decision-
making self-efficacy and had lower career indecision.
137
Regarding to perceived parental acceptance/ involvement, a second hypothesis that
perceived parental acceptance/ involvement would be indirectly related to career
indecision through career outcome expectations (Hypothesis 3b; Path 5 and Path
12). The findings of the current study confirmed the hypothesis 3b. There was a
small and positive indirect relationship between perceived parental acceptance/
involvement and career indecision through career outcome expectations.
Accordingly, pathways from perceived parental acceptance/ involvement to career
outcome expectations (Path 5) and from career outcome expectations to career
indecision (Path 12) were significant.
Concerning the indirect link between perceived parental strictness/ supervision and
career indecision two hypotheses were generated. It was hypothesis that perceived
parental strictness/ supervision would be related to career indecision indirectly
through career decision making self-efficacy (Hypothesis 4a; Path 6 and Path 11). In
addition, perceived parental strictness/ supervision would be related to career
indecision indirectly through career outcome expectations (Hypothesis 4b; Path 7
and Path 12). However, perceived parental strictness/ supervision was excluded from
the trimmed career indecision model due to nonsignificant pathways among
perceived parental strictness/ supervision, mediators and dependent variable of the
study. Thus, results of the study did not support both of the hypotheses. Similar to
present study, Ferry et al. (2000) and Rohner et al. (2009) reported that parental
control such a form of strictness/ supervision did not lead to any significant path in
their model. One of the explanation fort his finding might be that, as Akyıl (2000)
138
concluded samples from more educated segments of Turkey may value
independence, autonomy, and individuation more and perceive parental attitudes
which inhibit these values as rejecting. The same pattern may be valid for the current
sample as well.
Psychological autonomy was another perceived parental attitude included in the
current study. It was hypothesis that perceived parental psychological autonomy
would be related to career indecision indirectly through career decision-making self-
efficacy (Hypothesis 5a; Path 8 and Path 11). Findings revealed that there was a
small but significant indirect relationship between perceived parental psychological
autonomy and career indecision through career decision-making self-efficacy.
Hypothesized paths between perceived parental psychological autonomy and career
decision-making self-efficacy (Path 8), and between career decision-making self-
efficacy and career indecision (Path 11) were significant. Accordingly, perceived
parental psychological autonomy was positively related to career decision-making
self-efficacy which in turn, was negatively related to career indecision; participants
who had more perceived parental psychological autonomy had more career decision-
making self-efficacy and had lower career indecision. It was hypothesis that
perceived parental psychological autonomy would be related to career indecision
indirectly through career outcome expectations (Hypothesis 5b; Path 9 and Path 12).
Findings of the study, however, did not validate the hypothesis. Beyond hypotheses,
findings of the current study suggested a direct path from perceived parental
psychological autonomy to career indecision. Consistent with previous studies
139
(Guerra & Braungart-Rieker, 1999; Kinnier, et al., 1990; Tokar et al., 2003), parental
psychological autonomy moderately and negatively related to career indecision.
5.4 Hypothesized Relationships between Career Decision-Making Self-Efficacy
and Career Indecision
In the current investigation, two separate hypotheses were declared regarding the
relationship between career decision-making self-efficacy and career indecision. It
was hypothesized that career decision-making self-efficacy would be related to
career indecision directly (Hypothesis 6; Path 11). Findings revealed a large and
negative relationship between career decision-making self-efficacy and career
indecision. In other words, participants who had more career decision-making self-
efficacy had lower career indecision. Empirical research has previously investigated
the relations between career decision making self-efficacy and career indecision
consistently reported a moderate to high negative correlation between them (e.g.,
Betz, Hammond, & Multon, 2005; Taylor & Popma, 1990) as in the current study.
Further, it was hypothesized that career decision-making self-efficacy would be
related to career indecision indirectly through career outcome expectations
(Hypothesis 7, Path 10 and Path 12). The findings indicated a small but significant
indirect relationship between career decision-making self-efficacy and career
indecision suggested that the influence of career decision making self-efficacy on
career indecision operated through career outcome expectations. SCCT (Lent et al.,
1994) hypothesized that self-efficacy affects outcome expectations, with expectations
140
of positive outcomes increasing as beliefs in efficacy rise. Parallel to SCCT (Lent et
al., 1994) and prior studies (Lemon, 2010), a positive moderate direct relation was
observed between career decision-making self-efficacy and career outcome
expectations (Path 10) in this study.
5.5 Hypothesized Relationships between Career Outcome Expectations and
Career Indecision
It was hypothesized that career outcome expectations would be related to career
indecision directly (Hypothesis 8; Path 12). Results confirmed such a positive and
moderate direct relationship between career outcome expectations and career
indecision. However, the direction of the relationship was inconsistent with past
research. Previous studies (Betz & Klein-Voyten, 1997; Lemon, 2010; Weiss, 2000)
generally reported either a significant negative relationship or no significant
relationship between them. Outcome expectations about career decision-making
behaviors viewed as the beliefs that “those behaviors would be useful to subsequent
career options and decisions” (Betz & Klein-Voyten, 1997, p. 182). An explanation
for this finding might be that perceptions and interpretations of the participants
regarding the items of the Career Outcome Expectations Scale might have caused
this result.
A partial version of the Lent et al. (1994) model was examined in the present study.
The findings of this study suggested that locus of control and parental attitudes were
141
related to students‟ career indecision directly and indirectly through the career
decision-making self-efficacy in ways that are consistent with SCCT. Thus, results
based on the trimmed model provide support for the utility of SCCT in understanding
antecedents of career indecision. Self efficacy was the mostly investigated variables
in the previous model testing studies (e.g., Feldt & Woelfel, 2009; Huang, 1999;
Rogers et al., 2008) which mediating effect has been mostly verified. As in previous
studies mediating role of self-efficacy was confirmed in this study. Similar to Huang
(1999) and Wallace and Kindaichi (2005), parental variables related to career
indecision both directly and indirectly in the model that confirmed the hypothesis of
SCCT regarding contextual variables in the career decision-making process. As
proposed by Lent et al. (1994) and supported by Feldt and Woelfel (2009) outcome
expectations were significant predictor of career indecision in the model. The
explained variances in the present study were closed to previous investigations. For
example, Weiss (2000) model that included career-decision making self-efficacy,
career outcome expectations, and perceived barriers explained 37% of the variance in
career indecision.
5.6 Implications and Recommendations for Research and Practice
The study tested a model of career indecision based on SCCT (Lent et al., 1994) by
investigating the mediating role of career decision-making self-efficacy and career
outcome expectations between locus of control, perceived parental attitudes and
career indecision. Although the total variance explained by the trimmed model in
142
career indecision was not small, the rest could be explained by several other factors.
Without doubt, other intra-personal, interpersonal, and environmental factors which
were out of the scope of this study may also significantly impact the presence and
degree of career indecision of university students could be considered in future
studies.
The trimmed model formed in this study needs to be re-tested in other samples to
ensure that changes were not only representative of these particular participants. It
would also useful for future tests of the model to include more diverse samples
recruited from different type of universities including state and private from different
regions of Turkey.
In addition, career indecision was the only dependent variable in the current
investigation and a measure assessing the overall level of career indecision was used
(Osipow et al., 1987). Obviously, not all undecided students experience the same
kind of career indecision. Thus, as suggested Guay et al. (2006) examination of the
specific types of career indecision such as chronic and developmental indecision can
be suggested for future studies to get more detailed information about the nature of
career indecision experienced by university students. To achieve this, more valid and
reliable measures assessing different forms of career indecision are needed.
In this study locus of control, parental attitudes, career decision-making sellf-
efficacy, and career outcome expectations were examined to test partial utility of
143
SCCT. The findings of the current study validated the SCCT among a group of
Turkish university students. Accordingly, testing existed model with different
variables that were not investigated in the current study or developing new models
could be fruitful in explaining university students‟ career indecision.
Due to the self-report nature of the study, the findings have just relied on self-report
data which is typically associated with common respondent bias that leads to socially
desirable responses. There was only self-report measure for each of the variables
rather than from multiple perspectives (i.e. parents, friends, advisors). Thus, future
research may take into account using different types of measures to assess the
variables.
In the present study participants of the study composed of university students derived
from one of the high-ranking, prestigious and competitive university. Hence,
obtained findings can only be generalized to the similar populations. Even if the
sample of the current study represented all faculties and classes, it did not rely on one
of the random sampling that limits the generalizability of the findings. For further
studies, experience of career indecision should be examined in various populations
from different age groups to gather more information which allow making
comparisons between various samples.
Further, the findings of the present study provide implications for practice. One of
the findings of the current investigation was the high career indecision mean scores
144
among the participants of the study. Since this study was conducted in one of the
prestigious universities in Turkey, high career indecision among participants was an
unexpected finding. However, this finding is important in underlining the students‟
needs about provision of services about career indecision. Common services
provided by university career centers include; resume preparation, providing
information for jobs, providing information for job interviews and opportunities,
interview sessions, resume banks as well as job application, job placements and
career fairs (ErdoğmuĢ, 2001). Underlying assumption of these offered services is
that all students are decided and satisfied with their program and they only need
support from career centers before graduating to explore world of work and develop
their skills with regard to job application. However, as findings of the current study
indicated, career indecision might be an important issue for students and university
career centers can provide a broad range of services to students, in helping them to
deal with career indecision effectively.
Consistent with Lent et al.‟ (1994) theory, the hypothesized mediating role of career
decision-making self-efficacy was verified in this study. Considering the findings
from the current study, direct and mediating influences of career decision-making
self-efficacy on career indecision acknowledged as in past studies; it can be
concluded interventions either aiming at prevention or remediation to increase
students‟ career decision making self-efficacy, with an additional support on internal
locus of control can be beneficial for the undecided students. These interventions
could be composed of discussions, trainings, and assessments identifying internal
145
and external factors that influence career decision-making and career planning
process. For example, Brusoski, Golin, Gallagher, and Moore‟s (1993) intervention
that aimed to change the students‟ attributions by showing a video that emphasized
the individual‟s role in career planning was found to be effective.
Further implication of the findings may be related to the family. As stated by
researchers (Osipow, 1983; Roe, 1957; Super, 1957) parents influence career
decision-making process of their children. Likewise, the findings of the present study
suggested that family factors have an influence on university students‟ career
indecision. Students who experienced parental acceptance and a healthy separation
from parents seemed to be more decided on their career. Interventions that could
include families could be beneficial. However, in the current context, it seems not
practical. Rather, practitioners may try to enhance the awareness of students about
influences of perceived parental attitudes on their decisions.
Further, significant direct and indirect relations were obtained among locus of
control, parental acceptance/ involvement, parental psychological autonomy, and
career indecision. Thus, parallel to SCCT, interventions might best focus on helping
university students to understand the role of their family, personalitiy abilities,
values, and interests, and career decision-making self-efficacy in order to make more
accurate career decision.
146
REFERENCES
AbiĢeva, ġ. (1997). Eğitim Fakültesi öğrencilerinin meslek seçimini etkileyen bazı
etmenler [Some factors that effect the occupational choices of university
students in faculties of education].Unpublished master‟s thesis, Uludağ
University, Bursa.
Abu Talib, M., & Kit Aun, T. (2009). Predictors of career indecision among
Malaysian undergraduate students. European Journal of Social Sciences, 8,
215-224.
Ægisdóttir, S., Gerstein, L. H., & Canel-ÇınarbaĢ, D. (2008). Methodological issues
in cross-cultural counseling research: Equivalence, bias, and translations. The
Counseling Psychologist, 36, 188-219.
Ahn, J. (2002). Beyond single equation regression analysis: Path analysis and
multi stage regression analysis. American Journal of Pharmaceutical
Educational, 66, 37-42.
Akyıl, Y. (2000). Perceived parental child-rearing practices, and social anxiety in
Turkish university students. Unpublished master‟s thesis, Boğaziçi
University, Istanbul.
Amundson, N. E., Harris-Bowlsbey, J., & Niles, S. G. (2009). Essential elements
of career counseling: Processes and techniques. Upper Saddle River, NJ:
Pearson/Merrill Prentice Hall.
Arbuckle, J. L. (2009). AMOS 18 User’s Guide. Chicago: SPSS Inc.
147
Aydın, D. (2002). Grup rehberliğinin lise 1. sınıf öğrencilerinin alan tercihlerinde
gerçekçi davranmalarına etkisi [The effectiveness of a group guidance
program on the realistic field choice among first year high school students].
Unpublished doctoral dissertation, Ankara University, Ankara.
Bacanlı, F. (1995). Mesleki grup rehberliğinin lise öğrencilerinin mesleki
olgunluk düzeylerine etkisi [The effectiveness of a career group guidance
program on career maturity of high school students]. Unpublished doctoral
dissertation, Gazi University, Ankara.
Bacanlı, F. (2000). Kararsızlık Ölçeği‟nin geliĢtirilmesi [The development of
Indecisiveness Scale]. Türk Psikolojik Danışma ve Rehberlik Dergisi, 2(14),
7-16.
Bacanlı, F. (2006a). Career search self-efficacy expectation scale: Validity and
reliability studies. Kuram ve Uygulamada Eğitim Bilimleri, 6, 318-330.
Bacanlı, F. (2006b). Personality characteristics as predictors of personal
indecisiveness. Journal of Career Development, 32, 320-332.
Bacanlı, F. (2008, April). Career decision-making difficulties of Turkish
adolescents. Paper presented at the International Congress of Counseling,
Istanbul, Turkey.
Balın, E. (2008). The role of perceived career barriers and gender in predicting
commitment to career choices of university students. Unpublished master‟s
thesis, Middle East Technical University, Ankara.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral
change. Psychological Review, 84, 191-215.
148
Bandura, A. (1986). Social foundations of thought and action: A social cognitive
theory. Englewood Cliffs, NJ: Prentice-Hall.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction
in social psychological research: Conceptual, strategic and statistical
considerations. Journal of Personality and Social Psychology, 51, 1173-
1182.
Beck, A. T. (1987). Cognitive models of depression. Journal of Cognitive
Psychotherapy, 1, 5-37.
BektaĢ, D. Y. & Demir, A. (2004). Üniversite öğrencileri için mesleki grup
rehberliği programı ve programın etkisi üzerine bir çalıĢma [A study on
vocational guidance program for university students and the effectiveness of
the program]. Türk Psikolojik Danışma ve Rehberlik Dergisi, 3(22), 27-33.
Bentler, P. M. (1990). Comparative fit indexes in structural models.
Psychological Bulletin, 107, 238-246.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness-of-fit in
the analysis of covariance structures. Psychological Bulletin, 88, 588- 600.
Betz, N. E. (1992). Counseling uses of career self-efficacy theory. Career
Development Quarterly, 41, 22-26.
Betz, N. E., Fitzgerald, L. F, & Hill, R. E. (1989). Trait-factor theories: Traditional
cornerstone of career theory. In B. Michael, D. T. Hall, & B. S. Lawrence
(Eds.), Handbook of career theory (pp. 26–40). New York: Cambridge
University Press.
149
Betz, N. E., & Hackett, G. (1981). The relationship of career-related self- efficacy
expectations to perceived career options in college women and men. Journal
of Counseling Psychology, 28, 399-410.
Betz, N. E., Hammond, M. S., & Mukon, K. D. (2005). Reliability and validity of
five level response continua for the Career Decision Self-Efficacy
Scale. Journal of Career Assessment, 13, 131-149.
Betz, N. E., & Klein, K. (1996). Relationships among measures of career self-
efficacy, generalized self-efficacy, and global self-esteem. Journal of Career
Assessment, 4, 285–298.
Betz, N. E., & Klein Voyten, K. (1997). Efficacy and outcome expectations
influence career exploration and decidedness. Career Development
Quarterly, 46, 179-189.
Betz, N. E., Klein, K., & Taylor, K. (1996). Evaluation of a short form of the Career
Decision-Making Self-Efficacy Scale. Journal of Career Assessment, 4, 47-
57.
Blustein, D. L., Walbridge, M. M., Friedlander, M. L., & Palladino, D. E.
(1991). Contributions of psychological separation and parental attachment
to the career development process. Journal of Counseling Psychology,38,
39-50.
Bozgeyikli, H. (2005). Mesleki grup rehberliğinin ilköğretim 8. sınıf
öğrencilerinin meslek kararı vermede kendilerini yetkin görme düzeylerine
etkisi [The effectiveness of a career group guidance program on the career
decision making self-efficacy level of 8th
grade students]. Unpublished
doctoral dissertation, Selçuk University, Konya.
150
Bozgeyikli, H., Bacanlı, F., & Doğan, H. (2009). Ġlköğretim sekizinci sınıf
öğrencilerinin mesleki karar verme yetkinliklerinin yordayıcılarının
incelenmesi [An Examination of the predictors of career decision making
self-efficacy of 8th
grade students]. Selçuk Üniversitesi Sosyal Bilimler
Enstitüsü Dergisi, 21,125-136.
Bratcher, W. E. (1982). The influence of the family on career selection: A family
systems perspective. The Personnel and Guidance Journal, 61, 87-91.
Bronfenbrenner, U. (1977). Toward an experimental ecology of human
development. American Psychologist, 32, 513-530.
Brown, D. (1990). Summary, comparison, and critique of the major theories. In D.
Brown, L. Brooks, & Associates (Eds.), Career Choice and
Development (pp. 338-363). San Francisco: Jossey Bass.
Brown, D. (2002). The role of work and cultural values in occupational choice,
satisfaction, and success: A theoretical statement. Journal of Counseling
and Development, 80, 48-56.
Brown, D. (2003). Career information, career counseling, and career
development (8th ed.). Boston, MA: Allyn and Bacon.
Brusoski, G. C., Golin, A. K, Gallagher, R. P, & Moore, M. (1993). Career
group effects on career indecision: Career maturity, and locus of control of
undergraduate clients. Journal of Career Assessment, 1, 309-320.
Byrne, B. M. (2010). Structural equation modeling with AMOS: Basic concepts,
applications, and programming (2nd ed.). Madison, NY: Routledge.
151
Büyükgöze Kavas, A. (2005). Eğitim fakültesi öğrencilerinin aldıkları mesleki
rehberlik hizmetleri ve mesleklerini değiĢtirmek isteme düzeylerinin bazı
değiĢkenler açısından incelenmesi [An evaluation of education faculty
students‟ received vocational guidance services and the levels of changing
their career choice in terms of some variables]. Marmara Üniversitesi Atatürk
Eğitim Fakültesi Eğitim Bilimleri Dergisi, 21, 111-122.
Callahan, G. A., & Greenhaus, J. H. (1990). The career indecision of managers and
professionals: Development of a scale and test of a model. Journal of
Vocational Behavior, 37, 79-103.
Callahan, G. A., & Greenhaus, J. H. (1992). The career indecision of managers and
professionals: An examination of multiple subtypes. Journal of Vocational
Behavior, 41, 212-231.
Cattell, R. B. (1966). The scree test for the number of factors. Multivariate
Behavioral Research, 1, 245-276.
Cenkseven, F., Kırdök, O, & IĢık, E. (2008, April). Investigating career decisions
of high school students regarding to their parenting and parent attachment
styles. Paper presented at the International Congress of Counseling,
Istanbul, Turkey.
Chaney, D., Hammond, M. S., Betz, N. E., & Multon, K. D. (2007). The reliability
and factor structure of the Career Decision Self-Efficacy Scale- SF with
African Americans. Journal of Career Assessment, 15, 194-205.
Chartrand, J. M., Martin, W., Robbins, S., & McAuliffe, G. (1994). Testing a level
versus an interactional view of career indecision. Journal of Career
Assessment, 2, 55-69.
152
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159.
Corkin, D., Arbona, C., Coleman, M. N., & Ramirez, R. (2008). Dimensions of
career indecision among Hispanic college students. Journal of College
Student Development, 49, 81-94.
Constantine, M. G., & Flores, L. Y. (2006). Career-related mediators of perceived
family conflict and psychological distress in college students of color.
Journal of Career Assessment, 14, 354-369.
Constantine, M. G., Wallace, B. C., & Kindaichi, M. M. (2005). Examining
contextual factors in the career decision status of African American
adolescents. Journal of Career Assessment, 13, 307-319.
Cook, E. P., Heppner, M. J., & O‟Brien, K. M. (2002). Career development of
women of color and White women: Assumptions, conceptualization and
interventions from an ecological perspective. Career Development
Quarterly, 50, 291-305.
Coovert, M. D., & McNelis, K. (1988). Determining the number of common
factors in factor analysis: A review and program. Educational and
Psychological Measurement, 48, 687-692.
Cormier, S., & Nurius, P. S. (2003). Interviewing and change strategies for
helpers: Fundamental skills and cognitive behavioral interventions (5th
ed.). Pacific Grove, CA: Brookes-Cole.
Costello, A. B., & Osborne, J. (2005). Best practices in exploratory factor
analysis: Four recommendations for getting the most from your analysis.
Practical Assessment Research and Evaluation, 10(7), 1-10.
153
Creed, P. A., Patton, W, & Bartrum, D. (2004). Internal and external barriers,
cognitive style, and the career development variables of focus and
indecision. Journal of Career Development, 30, 277–294.
Creed, P.A., Patton, W., & Prideaux, L. (2006). Causal relationship between
career indecision and career decision-making self-efficacy: A
longitudinal cross-lagged analysis. Journal of Career Development, 33, 47-
65.
Creed, P. A., Patton, W., & Watson, M. (2002). Cross-cultural equivalence of the
Career Decision-Making Self-Efficacy Scale–Short Form: An Australian and
South African comparison. Journal of Career Assessment, 10, 327-342.
Crites, J. O. (1978). Theory and research handbook for the Career Maturity
Inventory (2nd Ed.) Monterey, CA: CTB/ McGraw-Hill.
Çakır, M. A. (2003). Bir mesleki grup rehberliği programının lise öğrencilerinin
mesleki kararsızlık düzeylerine etkisi [The effect of a career group guidance
program on the career indecision level of high school students]. Unpublished
doctoral dissertation, Ankara University, Ankara.
Daggit, J. A. (1996). The influence of perceived family dynamics on career
indecision in college students as a function of academic achievement
level, gender, and college class. Unpublished doctoral dissertation, University
of Iowa, Iowa.
Dağ, Ġ. (1991). Rotter‟in Ġç-DıĢ Kontrol Odağı Ölçeği‟nin (RĠDKOÖ) üniversite
öğrencileri için güvenirliği ve geçerliği [Reliability and validity studies of
Rotter‟s Internal External Locus of Control Scale for university students].
Psikoloji Dergisi, 7(26), 10-16.
154
Dawis, R. V. (2005). The Minnesota theory of work adjustment. In S. D. Brown &
R. T. Lent (Eds.), Career development and counseling: Putting theory and
research to work (pp. 3–23). Hoboken, NJ: Wiley.
Dawis, R. V., & Lofquist, L. H. (1984). A psychological theory of work adjustment.
Minneapolis, MN: University of Minnesota Press.
Dodge, T. D. (2001). An investigation of the relationship between the family of
origin and selected career development outcomes. Unpublished doctoral
dissertation, Louisiana Tech University, Ruston.
Duffy, R.D., & Lent, R.W. (2008). Relation of religious support to career
decision self-efficacy in college students. Journal of Career Assessment, 16,
360-369.
Durlanık, M. (1998). Bireysel danışma hizmetlerinin öğrencilerin mesleki
tercihlerine etkisi [The effect of individual counseling on occupational
choice of students]. Unpublished master‟s thesis, Selçuk University, Konya.
Edwards, J. R. (2008). Person-environment fit in organizations: An assessment of
theoretical progress. The Academy of Management Annals, 2, 167-230.
Efilti, E. (1998). Mesleki rehberliğin meslek seçimine etkisi üzerine bir araştırma
[An investigation of the effect of career guidance on occupational choice].
Unpublished master‟s thesis, Selçuk University, Konya.
Emmanuelle, V. (2009). Inter-relationships among attachment to mother and
father, self-esteem, and career indecision. Journal of Vocational Behavior,
75, 91-99.
155
ErdoğmuĢ, N. (2001). Üniversitelerdeki kariyer merkezlerinin etkinlikleri hakkında
bir araĢtırma [A research on services of universities‟ career centers]. Kuram
ve Uygulamada Eğitim Bilimleri, 1, 131-142.
Erikson, E. (1968). Identity, youth and crisis. New York: Norton.
Evren, M. (1999). Mesleki grup rehberliğinin cinsiyetleri farklı ilköğretim okulu
sekizinci sınıf öğrencilerinin mesleki olgunluklarına, mesleki benlik
algılarına ve mesleki tercihlerine etkisi [The effect of career group guidance
on career maturity, perceived occupational self, and occupational choice of
8th
grade students]. Unpublished master‟s thesis, Hacettepe University,
Ankara.
Feldt, R. C., Ferry, A., Bullock, M., Camarotti-Carvalho, A., Collingwood,
M.,…Woelfel, C. (2010). Factorial structure of the Career Decision Scale:
Incremental validity of the five factor domains. Measurement and Evaluation
in Counseling and Development, 42, 235-245.
Feldt, R. C., & Woelfel, C. (2009). Five-factor personality domains, self- efficacy,
career-outcome expectations, and career indecision. College Student
Journal, 43, 429-437.
Ferry, T. R., Fouad, N. A., & Smith, P. L. (2000). The role of family context in a
social cognitive model for career-related choice behavior: A math and
science perspective. Journal of Vocational Behavior, 57, 348-364.
Field, A. (2009). Discovering statistics using SPSS. (3rd ed.). Thousand Oaks, CA:
Sage Publications.
Fraenkel, J. R., & Wallen, N. E. (2006). How to design and evaluate research in
education (6th ed.). Boston, MA: The McGraw-Hill Companies.
156
Fuqua, D. R., Blum, C. R., & Hartman, B. W. (1988). Empirical support for the
differential diagnosis of career indecision. Career Developmental Quarterly,
36, 364-373.
Fuqua, D. R. & Hartman, B. W. (1983). Differential diagnosis and treatment of
career indecision. Personnel and Guidance Journal, 62, 27-29.
Fuqua, D. R., Seaworth, T. B., & Newman, J. L. (1987). The relationship of
career indecision and anxiety: A multivariate examination. Journal of
Vocational Behavior, 30, 175-186.
Garson, D. (2008). Structural equation modeling from statnotes: Topics in
multivariate analysis. North Carolina State University, Retrieved May 25,
2009.http://faculty.chass.ncsu.edu/garson/pa765/statnote.htm.
Gati, I., Krausz, M., & Osipow, S. H. (1996). A taxonomy of difficulties in
career decision making. Journal of Counseling Psychology, 43, 510-526.
Genç, G., Kaya, A., & Genç, M. (2007). Ġnönü Üniversitesi Tıp Fakültesi
öğrencilerinin meslek seçimini etkileyen faktörler [Factors that effect the
occupational choice of students of faculty of medicine]. Inönü Üniversitesi
Eğitim Fakültesi Dergisi, 8, 49-63.
George, D., & Mallery, P. (2001). SPSS for windows: Step by step (3rd ed.).
Boston: Allyn and Bacon.
Germeijs, V., & De Boeck, P. (2002). A measurement scale for indecisiveness and its
relationship to career indecision and other types of indecision. European
Journal of Psychological Assessment, 18, 113-122.
157
Gillespie, D., & Hillman, S. B. (1993, August). Impact of self-efficacy expectations
on adolescent career choice. Paper presented at the Annual Meeting of the
American Psychological Association, Toronto.
Gordon, V. N. (1995). The undecided college students: An academic and career
advising challenge (2nd ed.). Springfield, IL: Charles C Thomas.
Gottfredson, L. S. (1981). Circumscription and compromise: A developmental theory
of occupational aspirations. Journal of Counseling Psychology, 28, 545-579.
Gottfredson, L. S. (2005). Using Gottfredson's theory of circumscription and
compromise in career guidance and counseling. In S. D. Brown & R. W. Lent
(Eds.), Career development and counseling: Putting theory and research to
work (pp. 71-100). New York: Wiley.
Guay, F., Senécal, C., Gauthier, L., & Fernet, C. (2003). Predicting career
indecision: A self-determination theory perspective. Journal of Counseling
Psychology, 50, 165-177.
Guay, F., Ratelle, C. F., Senécal, C., Larose, S., & Deschenes, A. (2006).
Distinguishing developmental from chronic career indecision: Self-
efficacy, autonomy, and social support. Journal of Career Assessment, 14,
235-255.
Guerra, A. L., & Braungart-Rieker, J. M. (1999). Predicting career indecision in
college students: The roles of identity formation and parental relationship
factors. Career Development Quarterly, 47, 255-266.
158
Gysbers, N. C., Heppner, M. J., & Johnston, J. A. (2002). Career counseling,
process, issues, and techniques. (2nd ed.). Boston, MA: Allyn and
Bacon.
Hackett, G., & Betz, N. E. (1981). A self-efficacy approach to the career
development of women. Journal of Vocational Behavior, 18, 326-339.
Hackett, G. & Lent, R. W. (1992). Theoretical advances and current inquiry in
career psychology. In S. D. Brown & R. W. Lent (Eds.). Handbook of
Counseling Psychology (2nd Ed.) (pp. 419-452). New York: Wiley.
Hackett, G., Lent, R. W., & Greenhaus, J. H. (1991). Advances in vocational theory
and research: A 20-year retrospective. Journal of Vocational Behavior, 38, 3-
38.
Hair, J. F. J., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998).
Multivariate data analysis (5th ed.). Saddle River, NJ: Prentice Hall.
Hall, A. S., & Kelly, K. R. (1995). Effects of academic achievement, sex, and
community of residence on four types of career indecision. Journal of
Secondary Gifted Education, 7, 293-302.
Hamamcı, Z., & Esen Çoban, A . (2007). Mesleki olgunluk ve mesleki kararsızlığın
akılcı olmayan inançlarla iliĢkisi [Vocational maturity and career indecision
relations with irrational beliefs]. Türk Psikolojik Danışma ve Rehberlik
Dergisi, 3 (27), 31-42.
159
Hamamcı, Z., & Hamurlu, M. K. (2005). Anne babaların meslek geliĢimine yardımcı
olmaya yönelik tutumları ve bilgi düzeylerinin çocuklarının mesleki
kararsızlıkları ile iliĢkisi [Relationship between level of knowledge and
attitudes of parents about helping their children for career development and
career indecision of their children]. İnönü Üniversitesi Eğitim Fakültesi
Dergisi, 6, 55-69.
Hampton, N. Z. (2005). Testing for the structure of the Career Decision Self-
Efficacy Scale-Short Form among Chinese college students. Journal of
Career Assessment, 13, 98-113.
Hartung, P. J., & Niles, S. G. (2000). Using traditional career theories with college
students. In D. Luzzo (Ed.), Career development of college students:
Translating theory and research into practice (pp. 3-22). Washington, DC:
American Psychological Association.
Hawkins-Breaux, A. (2004). The impact of cooperative education participation on
career indecision, career decision-making self-efficacy and career decision
making style among college students. Unpublished doctoral dissertation, The
Temple University, Philadelphia.
Herr, E. L., Cramer, S. H., & Niles, S. G. (2004). Career guidance and counseling
through the lifespan: Systemic approaches (6th ed.). Boston: Allyn and
Bacon.
Hinkelmen, J. M. & Luzzo, D. A. (2007). Mental health and career development of
college students. Journal of Counseling and Development, 85, 143-147.
Holland, J. L. (1985). Manual for the Vocational Preference Inventory. Odessa, FL:
Psychological Assessment Resources, Inc.
160
Holland, J. L. (1997). Making vocational choices (3rd ed.). Odessa, FL:
Psychological Assessment Resources, Inc.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance
structure analysis: Conventional criteria versus new alternatives. Structural
Equation Modeling, 6, 1-55.
Huang, S. (1999). The effect of family environment, personality, and self-efficacy on
career indecision of college students. Unpublished doctoral dissertation,
Purdue University, West Lafayette.
Hutcheson, G., & Sofroniou, N. (1999). The multivariate social scientist:
Introductory statistics using generalized linear models. Thousand Oaks, CA:
Sage Publications.
IĢık, E. (2007, September). Üniversite öğrencilerinin üniversitelerinde verilen
kariyer danışmanlığı hizmetlerine ilişkin algı ve beklentileri [Perceptions and
expectations of the university students from the career counseling services
given at their university]. Paper presented at XVI. Ulusal Eğitim Bilimleri
Kongresi, GaziosmanpaĢa Üniversitesi, Tokat.
ĠĢmen Gazioğlu, A. E., Bekçi, B., Yavuz, Ç., & Çayırdağ, N. (2007). Ġstanbul ili özel
ve devlet okullarında mesleki rehberlik çalıĢmalarına iliĢkin durum
saptaması [Investigation of current status of vocational guidance activities in
state and private schools in Ġstanbul]. Eğitim Araştırmaları Dergisi, 27, 97-
109.
Jerusalem, M., & Schwarzer, R. (1981). Fragebogen zur Erfassung von
Selbstwirksamkeit. Skalen zur Befindlichkeit und Persoenlichkeit. In R.
Schwarzer (Hrsg.). (Forschungsbericht No. 5). Berlin: Freie
Universitaet, Institut fuer Psychologie.
161
Jin, L., Watkins, D., & Yuen, M. (2009). Personality, career decision self-
efficacy, and commitment to the career choices process among Chinese
graduate students. Journal of Vocational Behavior, 74, 47-52.
Jolley, M. T., & Spielberger, C. D. (1973). The effects of locus of control and
anxiety on verbal conditioning. Journal of Personality, 41, 443-456.
Kağnıcı, D. Y. (1999). Vocational maturity of METU preparatory school students.
Unpublished master‟s thesis. Middle East Technical University, Ankara.
Kaiser, H. F. (1970). A second generation little jiffy. Psychometrika, 35, 401-415.
Kang, A. E. (2009). Attachment, family conflict, and vocational self-concept in the
career indecision of Asian Americans. Unpublished doctoral
dissertation, Fordham University, New York.
Kazdin, R. I. (1976, August). Educational/ vocational indecision questionnaire:
replication of a factor analysis. Paper presented at the meeting of the
American Psychological Association, Washington, DC.
Kelly, K. R., & Pulver, C. A. (2003). Refining measurement of career indecision
types: A validity study. Journal of Counseling and Development, 81, 445-
454.
Kırdök, O. (2010). Bilişsel bilgiyi işleme yaklaşımına göre geliştirilen mesleki
karar verme programının sınanması [Testing a program of career decision
making based on Cognitive Information Processing Approach]. Unpublished
doctoral dissertation, Çukurova University, Adana.
162
Kinnier, R. T., Brigman, S. L., & Noble, F. C. (1990). Career indecision and
family enmeshment. Journal of Counseling and Development, 68, 309- 312.
Kline, R.B. (2005). Principles and practice of structural equation modeling (2nd
ed.). New York: Guilford Press.
Koç, M., (1991). K.T.Ü. Fatih Eğitim Fakültesi birinci sınıf öğrencilerin meslek
seçimlerine etki eden faktörlerin belirlenmesi [Determining the factors that
effect the occupational choice of freshmen of Fatih Education Faculty].
Unpublished master‟s thesis, Karadeniz Technical University, Trabzon.
Koçak, R., (2001). Orta öğretim okullarındaki mesleki rehberlik hizmetlerinin
değerlendirilmesi Gaziantep örneği [An evaluation of career guidance
services in secondary schools]. Unpublished master‟s thesis, Gaziantep
University, Gaziantep.
Korkut-Owen, F., Acar, T., Demir, Y., Haskan, Ö., Kabalcı, T., Kutsal, D.,
Pekin, Ġ. M., & Turan, E. (2009). Card sort techniques in vocational
guidance / career counseling: Pilot study about career values. İnönü
Üniversitesi Eğitim Fakültesi Dergisi, 10(2), 53-70.
Koydemir, S. (2006). Predictors of shyness among university students: Testing a
self-presentational model. Unpublished doctoral dissertation, Middle East
Technical University, Ankara.
Köksalan, B. (1999). Üniversite Öğrencilerinin Meslek Seçimini Etkileyen Bazı
Faktörler [Some factors that effect occupational choice of university
students]. Unpublished doctoral dissertation, Ġnönü University, Malatya.
Krumboltz, J. D., Mitchell, A. M., & Jones, G. B. (1976). A social learning
theory of career selection. The Counseling Psychologist, 6, 71-81.
163
Krumboltz, J. D., & Nichols, C. W. (1990). Integrating the social learning theory
of career decision making. In W. B. Walsh, & S. H. Osipow (Eds.),
Career counseling: Contemporary topics in vocational psychology
(pp.159-192). New Jersey, Lawrence Erlbaum Associates.
Lamborn, S., Mounts, N., Steinberg, L., & Dornbusch, S. (1991). Patterns of
competence and adjustment among adolescents from authoritative,
authoritarian, indulgent and neglectful homes. Child Development, 62,
1049-1065.
Ledesma, R. D., & Valero-Mora, P. M. (2007). Determining the number of
factors to retain in EFA: An easy-to-use computer program for carrying out
Parallel Analysis. Practical Assessment Research & Evaluation, 12,
(Art. No. 2). Retrieved February 18, 2011, from
http://pareonline.net/getvn.asp?v=12&n=2.
Lemon, R. L. (2010). African American women’s experiences of racist and sexist
events and their relations to the career choice process. Unpublished doctoral
dissertation, University of Akron, Ohio.
Lent, R. W. (2005). A social cognitive view of career development and counseling.
In S. D. Brown & R W. Lent (Eds.), Career development and counseling:
Putting theory and research to work (pp. 101-127). New York: Wiley.
Lent, R. W., & Brown, S. D. (1996). Social cognitive approach to career
development: An overview. Career Development Quarterly, 44, 310-321.
Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a unifying social
cognitive theory of career and academic interest, choice, and
performance [Monograph]. Journal of Vocational Behavior, 45, 79-122.
164
Lent, R. W., Brown, S. D., & Hackett, G. (1996). Career development from a
social cognitive perspective. In D. Brown, L. Brooks, and Associates
(Eds.), Career choice and development (3rd ed.) (pp. 373-421). San
Francisco: Jossey-Bass.
Lent, R. W., Brown, S. D., & Hackett, G. (2000). Contextual supports and
barriers to career choice: A social cognitive analysis. Journal of Counseling
Psychology, 47, 36-49.
Lent, R. W., Brown, S. D., Nota, L., & Soresi, S. (2003). Testing social cognitive
interest and choice hypotheses across Holland types in Italian high school
students. Journal of Vocational Behavior, 62, 101-118.
Lent, R.W., & Savickas, M.L. (1994). Postscript: Is convergence a viable agenda
for career psychology? In M. L Savickas & R. W. Lent (Eds.),
Convergence in career development theories: Implications for science and
practice (pp. 259-271). Palo Alto, CA: Consulting Psychologists Press.
Leong, F. T. L., & Chervinko, S. (1996). Construct validity of career indecision:
Negative personality traits as predictors of career indecision. Journal of
Career Assessment, 4, 315-329.
Loehlin, J. C. (2004). Latent variable models: an introduction to factor, path, and
structural equation analysis (4th ed). Mahwah: Lawrence Erlbaum.
Lofquist, L. H., & Dawis, R. V. (1991). Essentials of person environment
correspondence counseling. Minneapolis: University of Minnesota Press.
Lopez, F. G., & Andrews, S. (1987). Career indecision: A family system
perspective. Journal of Counseling and Development, 65, 304–307.
165
Lopez, F. G., & Ann-Yi, S. (2006). Predictors of career indecision in three
racial/ ethnic groups of college women. Journal of Career Development, 33,
29-46.
Luzzo, D. A. (1993). Reliability and validity testing of the Career Decision-
Making Self-Efficacy Scale. Measurement and Evaluation in Counseling and
Development, 26,137-142.
Luzzo, D. A. (Ed.). (2000). Career counseling of college students. Washington, DC:
American Psychological Association.
Luzzo, D. A., & Ward, B. E. (1995). The relative contributions of self-efficacy and
locus of control to the prediction of vocational congruence. Journal of
Career Development, 21, 307-317.
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and
determination of sample size for covariance structure modeling.
Psychological Methods, 1, 130-149.
Mann, L., Harmoni, R., & Power, C. (1989). Adolescent decision-making: The
development of competence. Journal of Adolescence, 12, 265-278.
Martin, F., Sabourin, S., Laplante, B., & Coallier, J. C. (1991). Diffusion,
support, approach, and external barriers as distinct theoretical dimensions
of the Career Decision Scale: Disconfirming evidence. Journal of Vocational
Behavior, 38, 187-197.
Mau, W. C. (1995). Decision-making styles as a predictor of career decision status
and treatment gains. Journal of Career Assessment, 3, 90-101.
166
Mau, W. C. (2001). Assessing career decision-making difficulties: A cross-
cultural study. Journal of Career Assessment, 9, 353-364.
Mathieu, P. S., Sowa, C. J., & Niles, S. G. (1993). Differences in career self-
efficacy among women. Journal of Career Development, 19, 187-196.
Mertler, C. A., & Vannatta, R. A. (2010). Advanced and multivariate statistical
methods: Practical application and interpretation (4th ed.). Glendale, CA:
Pyrczak Publishing.
METU (2008). General Catalog. Ankara: Middle East Technical University.
Mızıkacı, F. (2006). Higher Education in Turkey. Bucharest: CEPES/UNESCO.
Mitchell, L.K. & Krumbolt, J.D. (1996). Krumboltz's learning theory of career
choice and counseling In D. Brown, L. Brooks, & Associates (Eds.) (3rd ed).
Career choice and development. San Francisco, California: Jossey
Bass.
Mitchell, K. E., Levin, A. S., & Krumboltz, J. D. (1999). Planned happenstance:
Constructing unexpected career opportunities. Journal of Counseling and
Development, 77, 115-124.
Mocan-Aydın, G. (2000). Western models of counseling and psychotherapy
within Turkey: Crossing cultural boundaries. The Counseling
Psychologist, 28, 281-298.
Newman, J. L., Fuqua, D. R., & Minger, C. (1990). A discriminate study of
gender differences on career subscales. Paper presented at the 98th
Annual Convention of the American Psychological Association, Boston,
MA.
167
Ng, T. W. H., & Feldman, D. C. (2009). Personality, social relationships, and
vocational indecision among college students: The mediating effects of
identity construction. Career Development International, 14, 309-332.
Niles, S. C., & Harris-Bowlsbey, J. (2005). Career development interventions in the
21st century (2nd ed.). Upper Saddle River, NJ: Pearson Education Inc.
Niles, S. G., Hartung, P. J. (2000). Using emerging career theories with college
students. In D. Luzzo (Ed.), Career development of college students:
Translating theory and research into practice (pp. 23-42). Washington, DC:
American Psychological Association.
Nota, L., Ferrari, L., Solberg, V. S. H., & Soresi, S. (2007). Career search self-
efficacy, family support, and career indecision with Italian youth. Journal of
Career Assessment, 15, 181-193.
O‟Neil, J. M., Ohlde, C., Tollefson, N., Barke, C., Piggott, T., & Watts, D.
(1980). Factors, correlates, and problem areas affecting career-decision
making of cross-sectional sample of students. Journal of Counseling
Psychology, 27, 571-580.
Osipow, S. H. (1983). Theories of career development (3rd ed.). Englewood
Cliffs, NJ: Prentice-Hall.
Osipow, S. H. (1987). The Career Decision Scale manual. Odessa, FL:
Psychological Assessment Resources.
Osipow, S. H. (1990). Convergence in theories of career choice and
development. Journal of Vocational Behavior, 36, 122-131.
168
Osipow, S. H. (1996). Does career theory guide practice or does practice guide
theory? In M. L. Savickas & W. B. Walsh (Eds.). Handbook of career
counseling theory and practice (pp. 403-410). Palo Alto, CA: Davies-
Black.
Osipow, S. H. (1999). Assessing career indecision. Journal of Vocational
Behavior, 55, 147-154.
Osipow, S. H., Carney, C. G., & Barak, A. (1976). A scale of educational-
vocational undecidedness: A typological approach. Journal of Vocational
Behavior, 9, 233–243.
Osipow, S. H., Carney, C. G., Winer, J. L., Yanico, B., & Koschier, M. J.
(1976). The Career Decision Scale (3rd ed.). Odessa, FL: Psychological
Assessment Resources.
Osipow, S. H., & Fitzgerald, L. F. (1996). Theories of career development (4th ed.).
Needham Heights, Mass: Allyn and Bacon.
Osipow, S. H., & Reed, R. (1985). Decision making style and career indecision in
college students. Journal of Vocational Behavior, 27, 368-373.
Osipow, S. H., & Winer, J. L. (1996). The use of the Career Decision Scale in
career assessment. Journal of Career Assessment, 4, 117-130.
Öksüz, H. (2001). Mesleki grup rehberliğinin lise öğrencilerinin ilgi ve
yeteneklerine uygun alan seçmelerine etkisi [The effect of career group
guidance to high school students to choose field in accordance with their
interests and abilities]. Unpublished master‟s thesis, Gazi University,
Ankara.
169
Öğrenci Seçme ve YerleĢtirme Merkezi (2010). ÖSYS okul türü ve öğrenim
durumuna göre baĢvuran ve yerleĢen aday sayıları. Retrieved from
http://www.osym.gov.tr/belge/1-12381/yuksekogretime-giriste-okul-turu- ve-
ogrenim-durumuna-go-.html
Özyürek, R., Kılıç-Atıcı, M. (2002). Üniversite öğrencilerinin meslek seçimi
kararında kendilerine yardım eden kaynakların belirlenmesi [Determining the
helping sources of university students on their occupational decision]. Türk
Psikolojik Danışma ve Rehberlik Dergisi, 17, 33-42.
Page. J, Bruch. M, A., & Haase. R. F. (2008). Role of perfectionism and five-
factor model traits in career indecision. Personality and Individual
Differences, 45, 811 – 815.
Parsons, F. (1909). Choosing a vocation. Boston: Houghton Mifflin.
Patton W., & Lokan, J. (2001). Perspectives on Donald Super's construct of
career maturity, International Journal for Educational and Vocational
Guidance, 1, 31-48.
Pedhazur, E.J. (1997). Multiple regression in behavioral research, explanation and
prediction (3rd ed.). Orlando FL: Holt, Harcourt Brace & Company.
Peng, H., & Herr, E. L. (2002). Relation of career beliefs to career indecision
among distance education adult college students in Taiwan.
Psychological Reports, 90, 803-813.
Peterson, S. L., & delMas, R.C. (1998). The component structure of career
decision-making self-efficacy for underprepared college students. Journal of
Career Development, 24, 209-225.
170
Peterson, G. W., Sampson, J. P., Jr., Lenz, J. G., & Reardon, R. C. (2002).
Becoming career problem solvers and decision makers: A cognitive
information processing approach. In D. Brown (Ed.), Career choice and
development (pp. 312-369) (4th. Ed.). San Francisco, CA: Jossey-Bass.
Peterson, G. W., Sampson, J. P., Jr., & Reardon, R. C. (1991). Career
development and services: A cognitive approach. Pacific Grove, CA:
Brooks/Cole.
PiĢkin, M., & Gerçek, N. (2008, April). Career values of university students.
Paper presented at the International Congress of Counseling, Istanbul,
Turkey.
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for
assessing and comparing indirect effects in multiple mediator models.
Behavior Research Methods, 40, 879-891.
Quintana, S. M., & Maxwell, S. E. (1999). Implications of recent developments in
structural equation modeling for counseling psychology. The Counseling
Psychologist, 27, 485-527.
Roe, A. (1957). Early determinants of vocational choice. Journal counseling
Psychology, 4, 212-217.
Robbins, S. B. (1985). Validity estimates for the Career Decision-Making Self-
Efficacy Scale. Measurement and Evaluation in Counseling and
Development, 18, 64-71.
Rogers, M. E., Creed, P. A., & Glendon, A. I. (2008). The role of personality in
adolescent career planning and exploration: A social cognitive
perspective. Journal of Vocational Behavior, 73, 132-142.
171
Roger, W. B., & Westbrook, B. W. (1983). Measuring career indecision among
college students: Toward a valid approach for counseling practitioners and
researchers. Measurement and Evaluation in Guidance, 16, 78-85.
Rohner, R. P., Rising, D. G., & Sayre-Scibona, J. (2009). Sex differences in
relations among remembered parental behavior in childhood, adults'
current psychological adjustment, and career indecision. Psychological
Reports, 104, 558-566.
Rokeach, M. (1973). The nature of human values. New York: Free Press.
Rotter, J. (1966). Generalized expectancies for internal versus external control of
reinforcement. Psychological Monographs, 80(1), 1-28.
Sabourin, S., & Coallier, J. C. (1991). The relationship between response style and
reports of career indecision. Measurement and Evaluation in Counseling and
Development, 24, 69-79.
Saka, N., & Gati, I. (2007). Emotional and personality-related aspects of persistent
career decision-making difficulties. Journal of Vocational Behavior, 71, 340-
358.
Salomone, P. R. (1996). Tracing Super‟s theory of vocational development: A 40-
year retrospective. Journal of Career Development, 22, 167–184.
Sampson, J. P., Jr., Lenz, J. G., Reardon, R. C., & Peterson, G. W. (1999). A
cognitive information processing approach to employment problem
solving and decision making. The Career Development Quarterly, 48, 3- 18.
172
Sampson, J. P., Jr., Peterson, G. W., Lenz, J. G., & Reardon, R. C. (1992). A
cognitive approach to career services: Translating concepts into practice. The
Career Development Quarterly, 41, 67-74.
Santos, P. J., & Coimbra, J. L. (2000). Psychological separation and dimensions of
career indecision in secondary school students. Journal of Vocational
Behavior, 56, 346–362.
Sarıkaya, T., & Khorshid, L. (2009). Üniversite öğrencilerinin meslek seçimini
etkileyen etmenlerin incelenmesi: Üniversite öğrencilerinin meslek
seçimi [the investigation of the factors that affect university students‟
profession choice: University students‟ profession choice]. Türk Eğitim
Bilimleri Dergisi, 7, 393-423.
Saunders, D. E. (1997). The contribution of depression and dysfunctional career
thinking to career indecision. Unpublished doctoral dissertation, The Florida
State University, Tallahassee.
Saunders, D. E., Peterson, G. W., Sampson, J. P., Jr., & Reardon, R. C. (2000).
Relation of depression and dysfunctional career thinking to career
indecision. Journal of Vocational Behavior, 56, 288-298.
Savickas, M. L. (2005). The theory and practice of career construction. In S. D.
Brown, R. W. Lent (Eds.), Career development and counseling: Putting
theory and research to work (pp. 42-69). New Jersey, USA: John Wiley &
Sons Inc.
Savickas, M. L., & Carden, A. D. (1992). Dimensions of career decidedness.
Measurement and Evaluation in Counseling and Development, 25(3),
102-113.
173
Schulenberg, J. E., Shimizu, K., Vondracek, F. W., & Hostetler, M. (1988).
Factorial invariance of career indecision dimensions across junior high-
school and high-school males and females. Journal of Vocational Behavior,
33, 63-81.
Schumacker, R. E., & Lomax, R. G. (2004). A Beginner’s Guide to Structural
equation Modeling. Mahwah, New Jersey: Lawrence Erlbaum Associates,
Publishers.
Sharf, R. S. (2006). Applying career development theory to counseling (4th ed.).
Belmont, CA: Thomson Wadworth.
Shimizu, K., Vondracek, F. W., Schulenberg, J. E., & Hostetler, M. (1988). The
factor structure of the Career Decision Scale: Similarities across selected
studies. Journal of Vocational Behavior, 32, 213-225.
Simon, M. A. (1990). Career indecision in graduate business students: Correlates
and moderators. Unpublished doctoral dissertation, University of Southern
California.
Slaney, R. B., Palko-Nonemaker, D., & Alexander, R. (1981). An investigation of
two measures of career indecision. Journal of Vocational Behavior, 18, 92-
103.
Stage, F. K., Carter, H. & Nora, A. (2004). Path analysis: An introduction and
analysis of a decade of research. Journal of Educational Research, 98, 5-
12.
174
Staley, W. (1996). The relationship between fear of success, self-concept, and
career decision making. Paper presented at the Annual Meeting of the
Mid-South Educational Research Association Tuscaloosa, AL: EDRS.
Stead, G. B., Watson, M. B., & Foxcroft, C. D. (1993). The relation between
career indecision and irrational beliefs among university students. Journal of
Vocational Behavior, 42, 155-169.
Stevens, J. P. (2002). Applied multivariate statistics for the social sciences (4th ed.).
Manwah, NJ: Lawrence Erlbaum Associates, Inc.
Super, D. (1957). The psychology of careers. New York: Harper.
Super, D. E. (1980). A life-span, life-space approach to career development.
Journal of Vocational Behavior, 16, 282-298.
Super, D. E. (1990). A life-span, life-space approach to career development. In D.
Brown & L. Brooks (Eds.), Career choice and development: Applying
contemporary approaches to practice (2nd ed., pp. 197–261). San Francisco,
CA: Jossey-Bass.
Swanson, J. L., & Fouad, N. A. (1999). Career theory and practice: Learning
through case studies. CA: SAGE Publications, Inc.
Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics (5th
ed.) Boston: Allyn and Bacon.
Tang, M., Fouad, N. A., & Smith, P. L. (1999). Asian Americans‟ career choices: A
path model to examine factors influencing their career choices. Journal of
Vocational Behavior, 54, 142-157.
175
Taylor, K. M. (1982). An investigation of vocational indecision in college
students: Correlates and moderators. Journal of Vocational Behavior, 21,
318-329.
Taylor, K. M., & Betz, N. E. (1983). Applications of self-efficacy theory to the
understanding and treatment of career indecision. Journal of Vocational
Behavior, 22, 63-81.
Taylor, K. M., & Popma, J. (1990). Construct validity of the Career Decision-
Making Self-Efficacy Scale and the relationship of CDMSE to vocational
indecision. Journal of Vocational Behavior, 37, 17-31.
Tokar, D. M., Withrow, J. R., Hall, R. J., & Moradi, B. (2003). Psychological
separation, attachment security, vocational self-concept crystallization, and
career indecision: A structural equation analysis. Journal of Counseling
Psychology, 50, 3-19.
Trochim, W., & Donnelly, J. P. (2007). The research methods knowledge base (3rd
ed.). Mason, OH: Thomson Publishing.
Ulu, E. (2007). Lise öğrencilerinin kariyer inançlarının bazı değişkenlere göre
yordanması [Predictors of high school students‟ career beliefs]. Unpublished
master‟s thesis. Ege University, Ġzmir.
Uskaner, A. (1999). Mesleki grup rehberliğinin lise birinci sınıf ğrencilerinin
mesleki olgunluk düzeylerine etkisi [The effect of career group guidance on
career maturity of high school students]. Unpublished master‟s thesis,
Çukurova University, Adana.
176
Uysal, F. (2001). Kariyer mesleklerinden akademisyenliğin tercihinde ailenin
rolü: Hacettepe Üniversitesi örneği [The role of the family for the choice of
becoming an academician among the professional sobs: the example of the
Hacettepe University].Unpublished master‟s thesis, Hacettepe University,
Ankara.
Van de Vijver, F. J. R., & Hambleton, R. K. (1996). Translating tests: Some practical
guidelines. European Psychologist, 1, 89-99.
Vondracek, F. W., Lerner, R. M., & Schulenberg, J. E. (1986). Career
development: A life-span developmental approach. Hillsdale, NJ: Erlbaum
Associates.
Walsh, W. B., & Osipow, S. H. (Ed.). (1990). Career counseling: Contemporary
topics in vocational psychology. Hillsdale, NJ: Lawrence Erlbaum
Associates, Publishers.
Watson, M. B., Brand, H. J., Stead, G. B., & Ellis, R. R. (2001). Confirmatory
factor analysis of the Career Decision-Making Self-Efficacy Scale among
South African university students. Journal of Industrial Psychology, 27, 43-
46.
Weiss, K. I. (2000). The social cognitive model of career choice: A cross cultural
analysis. Unpublished doctoral dissertation, State University of NewYork,
Buffalo.
Weston, R., & Gore, P. A. Jr. (2006). A brief guide to structural equation modeling.
The Counseling Psychologist, 34, 719-751.
177
Whiston, S. C., & Keller, B. K. (2004). The influences of the family of origin on
career development: A review and analysis. The Counseling
Psychologist, 32, 493-568.
Williams, J., & MacKinnon, D. P. (2008). Resampling and distribution of the
product methods for testing indirect effects in complex models. Structural
Equation Modeling, 15, 23-51.
Woodbury, C. A., (1997). The relationship of anxiety, locus of control and hope
to career indecision of African American students. Unpublished doctoral
dissertation, Horward University, Washington.
Yerin Güneri, O., Owen, D., Tanrıkulu, Ġ., Dolunay, F., & Büyükgöze Kavas, A.
(2009, October). Eğitim fakültesi ögrencilerinin kariyer gelişimi
ihtiyaçlarinin incelenmesi [Examination of the career development needs of
students of education faculty]. A paper presented at X. Ulusal Psikolojik
DanıĢma ve Rehberlik Kongresi, Çukurova Üniversitesi, Adana.
Yılmaz, A. (2000). Eşler arasındaki uyum ve çocuğun algıladığı anne-baba
tutumu ile çocukların, ergenlerin ve gençlerin akademik başarıları ve
benlik arasındaki ilişkiler [Relationships between marital adjustment, child
perception of parenting style, and childrens‟, adolescents‟, and young adults‟
academic achievement and self-perceptions]. Unpublished doctoral
dissertation, Hacettepe University, Ankara.
Yılmaz Erdem, A., & Bilge, F. (2008). Lise öğrencileri için meslek seçimine iliĢkin
akılcı olmayan inançlar ölçeğinin geliĢtirilmesi [The scale for irrational
beliefs in career choices of high school students]. Türk Psikolojik Danışma ve
Rehberlik Dergisi,3(29), 95-110.
178
Zunker, V. G. (2002). Career counseling: Applied concepts of life planning.
Pasific Grove, CA: Thomson Brooks/ Cole, Publishers.
Zunker, V. G. (2006). Career counseling a holistic approach. Belmont, CA:
Thomson Brooks/ Cole, Publishers.
Zunker, V. (2008). Career, work, and mental health: Integrating career and
personal counseling. Thousand Oaks, CA: SAGE Publications Inc.
179
APPENDICES
180
APPENDIX A
DEMOGRAPHIC INFORMATION FORM
(DEMOGRAFĠK BĠLGĠ FORMU)
Değerli Katılımcı,
Bu çalıĢma, üniversite öğrencilerinin kariyer seçimlerinde karĢılaĢtıkları kararsızlığı
etkileyen değiĢkenlerin anlaĢılmasına yönelik olarak yapılmaktadır. Sizden istenilen
ölçeklerdeki tüm maddeleri sizin gerçek durumunuzu belirtecek Ģekilde yanıtlamanızdır.
AraĢtırma sonuçları grup olarak değerlendirileceğinden ad-soyad gibi kimliğinizi
belirtecek bilgileri yazmanıza gerek yoktur. Yanıtlarınız kesinlikle gizli tutulacak ve
sadece araĢtırma kapsamında kullanılacaktır. Katkılarınızdan dolayı Ģimdiden teĢekkür
ederim.
AraĢ.Gör. AyĢenur Büyükgöze Kavas
ODTÜ, Eğitim Bilimleri Bölümü
Tel: 2104034, e-posta: [email protected]
1. Cinsiyetiniz: ( ) Kız ( ) Erkek
2. YaĢınız:……..
3. Genel Akademik Ortalamanız: (CumGPA):
4. Sınıfınız: ( ) 1
( ) 2
( ) 3
( ) 4
( ) Diğer (Lütfen belirtiniz)………………
5. Fakülteniz: ( ) Eğitim Fakültesi
( ) Ġktisadi ve Ġdari Bilimler Fakültesi
( ) Fen-Edebiyat Fakültesi
( ) Mimarlık Fakültesi
( ) Mühendislik Fakültesi
6. Bölümünüz:……………………………………………………
181
APPENDIX B
SAMPLE ITEMS OF CAREER DECISION SCALE*
(KARĠYER KARAR ÖLÇEĞĠ ÖRNEK MADDELERĠ)
Bu ölçek insanların eğitim ve mesleki planlarına iliĢkin genel olarak dile getirdikleri
bazı ifadeleri içermektedir. Bu ifadelerden bazıları size uygun olabilir; bazıları ise
olmayabilir. Lütfen ifadelerin tümünü okuyunuz ve her bir maddenin sizin kariyer ya da
eğitim ile ilgili bir seçime iliĢkin düĢüncelerinize ne kadar yakın olduğunu, uygun olan
rakamı iĢaretleyerek belirtiniz. AĢağıda bir örnek verilmiĢtir.
Eğer bir iĢte çalıĢmaya baĢlama konusunda heyecanlıysanız ve bu konuda herhangi
bir tereddüttünüz yoksa tanımın tam olarak sizin duygunuzu yansıttığını belirtmek için “4”
rakamını iĢaretleyiniz. Eğer madde sizin duygunuza yakın ancak tam olarak ne hissettiğinizi
yansıtmıyorsa, örneğin mezun olduktan sonra çalıĢmaya baĢlamak için genelde heyecan
duyuyorsanız ama bu konu hakkında bazı ufak tefek kaygılar da yaĢıyorsanız “3” rakamını
iĢaretleyiniz. Eğer madde sizi bazı yönlerden tanımlıyor, fakat genel olarak sizin
duygularınızdan farklı ise, örneğin mezuniyetten sonra çalıĢma konusunda istekli olmaktan
daha çok endiĢeliyseniz “2”yi iĢaretleyiniz. Son olarak madde eğer sizin duygularınızı hiçbir
Ģekilde tanımlamıyorsa; yani mezuniyet ya da çalıĢma konusunda büyük ölçüde endiĢe
taĢıyor ve heyecan duymuyorsanız “1”i iĢaretleyiniz. Lütfen her bir maddeye sadece bir
cevap verdiğinizden ve tüm maddeleri cevapladığınızdan emin olunuz.
* According to publisher agreement, only two sample items are illustrated.
1.
Ben
i
tam
am
ıyla
ya
nsıtıy
or
Ben
i bü
yü
k
ölç
üd
e
ya
nsıtıy
or
Ben
i sad
ece
bir
az
ya
nsıtıy
or
Ben
i hiç
ya
nsıtm
ıyo
r
1. Mezun olma ve iĢe baĢlama konusunda
heyecanlıyım.
2.
Ben
i
tam
am
ıyla
ya
nsıtıy
or
Ben
i bü
yü
k
ölçü
de
ya
nsıtıy
or
Ben
i sad
ece
bira
z
ya
nsıtıy
or
Ben
i hiç
ya
nsıtm
ıyo
r
3. 1. Eninde sonunda iĢe girmek zorunda olacağımı biliyorum.
Fakat bildiğim kariyer alanlarının hiçbirisi bana cazip
gelmiyor.
2. Bir kariyer alanını seçmeyle ilgili her Ģey çok belirsiz
göründüğü için cesaretimin kırıldığını hissediyorum.
Öylesine cesaretim kırıldı ki Ģu an için bir karar vermek
istemiyorum.
182
APPENDIX C
SAMPLE ITEMS OF CAREER DECISION SELF-EFFICACY SCALE
SHORT-FORM
(KARĠYER KARARI ÖZ-YETERLĠK ÖLÇEĞĠ KISA-FORM
ÖRNEK MADDELERĠ)
AĢağıdaki her bir ifadeyi, lütfen dikkatle okuyunuz ve bu ifadelerdeki iĢlerin her birini
baĢarabileceğinize iliĢkin kendinize ne derece güvendiğinizi, verilen derecelendirme
sistemine göre iĢaretleyerek belirtiniz.
AĢağıdaki maddelerde belirtilen her bir
konuda kendinize ne kadar
güveniyorsunuz?
Hiç
Gü
ven
miy
oru
m
Ço
k a
z
Gü
ven
iyo
rum
Bira
z
Gü
ven
iyo
rum
Ço
k
Gü
ven
iyo
rum
Ta
ma
men
Gü
ven
iyo
rum
1. Ġlgilendiğiniz meslekler hakkında bilgi
edinmek için interneti kullanma
2. DüĢündüğünüz olası kariyer alanlardan
birini seçme
3. Ġyi bir özgeçmiĢ hazırlama
4. Gelecek on yıl için mesleğinizdeki
istihdam eiğilimlerini görme
183
APPENDIX D
SAMPLE ITEMS OF CAREER OUTCOME EXPECTATIONS SCALE
(KARĠYER SONUÇ BEKLENTĠLERĠ ÖLÇEĞĠ
ÖRNEK MADDELERĠ)
AĢağıdaki maddeler üniversite öğrencilerinin kariyer planlarına yönelik tutumlarıyla ilgilidir.
Lütfen her bir ifadeyi dikkatle okuyunuz. Daha sonra her bir ifadeye ne kadar çok
katıldığınıza veya katılmadığınıza karar veriniz. Cevaplarınızı her bir soru numarasına denk
gelen sıradaki dairelerden birisini iĢaretleyerek belirtiniz. Cevabınızdaki numara her ifadenin
sizi ve duygularınızı Ģu an ne ölçüde tanımladığını göstermektedir. Doğru veya yanlıĢ cevap
yoktur.
Kesin
likle
Ka
tılmıy
oru
m
Ka
tılmıy
oru
m
Ka
rarsızım
Ka
tılıyo
rum
Kesin
likle
Ka
tılıyo
rum
1. Eğer farklı kariyer seçenekleri hakkında daha çok
bilgi sahibi olursam, daha iyi bir kariyer kararı
verebileceğim.
2. Eğer farklı kariyerler için ihtiyacım olan eğitimi
bilirsem, daha iyi bir kariyer seçimi yapabileceğim.
3. Eğer ilgilerimi ve yeteneklerimi bilirsem,
kendime uygun bir kariyer seçebilirim.
4. Eğer kariyerler hakkında bilgi toplamak için
5. yeterince zaman harcarsam, iyi bir karar vermek
6. için neleri bilmem gerektiğini öğrenebilirim.
184
APPENDIX E
SAMPLE ITEMS OF PARENTAL ATTITUDES SCALE
(ANNE-BABA TUTUM ÖLÇEĞĠ ÖRNEK MADDELERĠ)
AĢağıda anne ve babanızın sizinle ilgili olarak sergilemiĢ olduğu bazı davranıĢlara ait
ifadeler yer almaktadır. Lütfen üniversiteye kadar olan yaĢamınızı düĢünerek bu
davranıĢların, ailenizin size karĢı olan davranıĢlarını ne derece yansıttığını verilen
derecelendirme sistemine göre belirtiniz.
Hiç
Ben
zemiy
or
Ben
zemiy
or
Bira
z
Ben
ziyo
r
Ta
mam
en
Ben
ziyo
r
1. Herhangi bir sorunum olduğunda annem ve babam bana
yardım ederdi.
2. Annem ve babam büyüklerle tartıĢmamam gerektiğini
söylerdi.
3. Annem ve babam yaptığım her Ģeyin en iyisini yapmam
için beni zorlardı.
4. Derslerimden düĢük not aldığımda, annem ve babam
beni daha çok çalıĢmam için desteklerdi.
185
APPENDIX F
SAMPLE ITEMS OF ROTTER’S INTERNAL EXTERNAL LOCUS OF
CONTROL SCALE
(ROTTER ĠÇSEL-DIġSAL KONTROL ODAĞI ÖLÇEĞĠ
ÖRNEK MADDELERĠ)
Bu anket, bazı önemli olayların insanları etkileme biçimini bulmayı amaçlamaktadır.
Her maddede „a‟ ya da „b‟ harfleriyle gösterilen iki seçenek bulunmaktadır. Lütfen, her
seçenek çiftinde sizin kendi görüĢünüze göre gerçeği yansıttığına en çok inandığınız cümleyi
(yalnız bir cümleyi) seçiniz ve iĢaretleyiniz.
Seçiminizi yaparken, seçmeniz gerektiğini düĢündüğünüz veya doğru olmasını arzu
ettiğiniz cümleyi değil, gerçekten daha doğru olduğuna inandığınız cümleyi seçiniz. Bu
anket kiĢisel inançlarla ilgilidir; bunun için „doğru‟ ya da „yanlıĢ‟ cevap diye bir durum söz
konusu değildir.
1. a
Ġnsanlar bu dünyada hak ettikleri saygıyı er geç görürler.
b Ġnsan ne kadar çabalarsa çabalasın ne yazık ki değeri genellikle anlaĢılmaz.
2. a Ġnsanların yaĢamındaki mutsuzlukların çoğu, biraz da Ģanssızlıklarına
bağlıdır.
b Ġnsanların talihsizlikleri kendi hatalarının sonucudur.
3. a Hiç bir yönü iyi olmayan insanlar vardır.
b Herkesin iyi tarafı vardır.
4. a Benim açımdan istediğimi elde etmenin talihle bir ilgisi yoktur.
b Çoğu durumda, yazı-tura atarak da isabetli kararlar verilebilir.
186
APPENDIX G
TURKISH SUMMARY
TÜRKÇE ÖZET
SOSYAL BĠLĠġSEL KARĠYER KURAMINA DAYALI BĠR KARĠYER
KARARSIZLIĞI MODELĠNĠN ÜNĠVERSĠTE ÖĞRENCĠLERĠNDE
SINANMASI
GĠRĠġ
YaĢamdaki önemli ve kaçınılmaz görevlerden birisi de meslek seçimidir. Özellikle
üniversite yılları, gençlerin gelecekteki kariyerlerine iliĢkin önemli kararları aldıkları
kritik bir dönemdir. Bu dönemde kariyere iliĢkin alınan kararların gençlerin mesleki
geleceğini, psikolojik ve fiziksel iyilik halini, sosyal kabulünü dolayısıyla genel
yaĢam kalitesini etkilemesi (Mann, Harmoni, & Power, 1989), bu kararları zor ve
karmaĢık bir hale getirmektedir (Gati, Krausz & Osipow, 1996). Bu nedenle, kariyer
kararsızlığı üniversitelerin psikolojik danıĢma merkezlerine baĢvuran öğrencilerin
sıklıkla belirttikleri problemlerden birisi olarak ortaya çıkmakta (Kelly & Pulver,
2003) ve üniversite öğrencilerinde %20 ile %60 arasında değiĢen oranlarda kariyer
kararsızlığı görülmektedir (Gordon, 1995). Günümüzde, birçok ekonomik ve
psikolojik sonucu da beraberinde getiren kariyer konusunda kararsızlık, birçok
araĢtırmacının ilgisini çeken popüler konulardan birisi haline gelmiĢtir (Betz, 1992;
Osipow, 1999).
187
Kariyer kararsızlığı terimi genellikle kariyer geliĢimi ile ilgili problemleri, özellikle
kariyer ile ilgili kararlar alınırken karĢılaĢılan problemleri ifade etmek için
kullanılmaktadır. Ayrıca, kariyer kararsızlığı, mesleki olgunluk sürecinde kiĢinin
kendisi ya da iĢ dünyası hakkındaki bilgi eksikliğinden kaynaklanan geliĢimsel bir
problem olarak da görülmektedir (Chartrand vd., 1994). Hawkins-Breaux (2004)
kariyer kararsızlığını genel olarak “bireyin kariyer geliĢim sürecinde karar vermesi
veya geleceği için eylemde bulunması gerektiğinde bazı sebeplerden dolayı bu
süreçte ilerleyememesi” Ģeklinde tanımlamıĢtır. Sonuç olarak, kariyer kararsızlığı
bireyin kariyer seçimleri hakkında yaĢadığı yoğun belirsizlik duygusunu beraberinde
getiren ciddi bir problem olarak görülmektedir.
Kariyer kararsızlığının ve onunla iliĢkili değiĢkenlerin anlaĢılması için birçok
çalıĢma yapılmıĢtır. Bu çalıĢmalarda çoğunlukla kariyeri hakkında kararlı ve kararsız
öğrencilerin ayırtedici kiĢilik faktörleri üzerinde odaklanmıĢtır. Bu etkenler arasında,
kontrol odağı (Fuqua & Hartman, 1983; Taylor, 1982), kaygı (Newman, Fuqua &
Minger, 1990) öz-yeterlik (Betz & Voyten, 1997; Taylor & Betz, 1983), mesleki
olgunluk (Fuqua vd., 1988), akılcı olmayan inançlar, baĢarısızlık korkusu (Taylor,
1982), benlik saygısı (Creed vd., 2004), kiĢilik oluĢumu (Tokar vd., 2003),
mükemmeliyetçilik, bağlanma korkusu (Leong & Chervinko, 1996), depresyon
(Saunders vd., 2000) ve karamsarlık (Saka & Gati, 2007) gibi birçok kiĢilik özelliği
çalıĢılmıĢtır. Bulgular genellikle kararsız öğrencilerin kararlı öğrencilere nispeten
daha kaygılı, bağımlı, dıĢsal kontrollü ve düĢük özyeterliğe sahip olduğunu rapor
etmektedir.
188
KiĢilik özelliklerine ek olarak, birçok kuramcı (Roe, 1957) ve araĢtırmacı (Blustein
vd., 1991; Lopez & Andrews, 1987) ailevi faktörlerin bireylerin kariyer kararları
üzerindeki etkilerini vurgulamaktadır. Örneğin, O‟Neil vd., (1980) bir grup genç
yetiĢkin ile yaptıkları çalıĢmada, katılımcıların %50‟si kariyerleri ile ilgili karar
verme sürecinde ailelerinin oldukça etkili olduğunu belirtmiĢlerdir. Benzer olarak,
Büyükgöze-Kavas (2005) ve IĢık (2007) üniversite öğrencileri ile yaptıkları
çalıĢmalarında ailenin öğrencilerin kariyer kararı verme sürecinde en etkili
faktörlerden birisi olduğunu ifade etmiĢlerdir. Bratcher‟e göre (1982) aileler, aile
bütünlüğünü sağlamak için bazı kurallar geliĢtirirler. Böylece, bu kurallar kariyer
kararı verme davranıĢları da dahil olmak üzere bireyin tüm davranıĢlarını etkiler.
Lopez ve Andrews (1987) ise, gençlerin kariyer kararsızlığını birey ve ailesi
arasındaki oldukça geniĢ bir etkileĢimin sonucu olarak görmektedir. Whiston ve
Keller (2004) ailevi değiĢkenlerin kariyer geliĢimindeki rolünü inceleyen nitel ve
nicel çalıĢma sonuçlarını derledikleri çalıĢmalarında, üniversite öğrencilerinin ve
genç yetiĢkinlerin kariyerleri hakkında karar verirken anne ve babadan alınan
duygusal destek, anne babanın psikolojik özerklik desteği, cesaretlendirmesi ve anne
babanın kabul edici tutumlarının etkili olduğu sonucuna varmıĢlardır.
Kariyer kararsızlığını araĢtıran çalıĢmalarda cinsiyet ve yaĢ gibi değiĢkenlerin
sıklıkla incelendiği dikkat çekmektedir. Önceki çalıĢmalar genellikle kariyer
kararsızlığında cinsiyet farkı olmadığını göstermektedir. Diğer taraftan çalıĢmaların
çoğu, kariyer kararsızlığı ve yaĢ arasında olumsuz bir iliĢki olduğunu göstermektedir.
189
Günümüze kadar bireylerin kariyer karar verme sürecini anlamaya ve açıklamaya
çalıĢan birçok kariyer seçimi ve geliĢimi kuramı geliĢtirilmiĢtir. Ancak bu kuramların
çoğu genellikle bireysellik ve kendini gerçekleĢtirme gibi batı kaynaklı değerleri
yansıttıkları için eleĢtirilmektedirler. Amerika BirleĢik Devletleri‟nin nüfusundaki
azınlıkların önemli artıĢı ve kültürler arası yoğun etkileĢim ve iletiĢim birçok
kuramın değiĢik kültürel gruplar için tekrar gözden geçirilmesine yol açmıĢtır. Son
yıllarda araĢtırmacılar birçok etkileĢimli faktörün, çevresel durumların ve koĢulların
kariyer kararı verme sürecinde önemli bir yeri olduğunu vurgulamaktadır. Bu
geliĢmelere paralel olarak, Sosyal BiliĢsel Kariyer Kuramı bireyin kariyer seçimi ve
geliĢimini etkileyebilecek kiĢisel, ailesel, kültürel ve çevresel faktörleri geniĢ bir
çerçevede ele alınmasını ve değerlendirilmesini sağlayan kapsamlı bir yapıya sahip
olan ve son yıllarda akademik ve kariyer geliĢimini açıklamaya yönelik çağdaĢ
yaklaĢımlardan biri olarak sıklıkla kullanılmaya baĢlamıĢtır. Sosyal BiliĢsel Kariyer
Kuramı bu çalıĢmanın da kuramsal temelini oluĢturmaktadır.
Sosyal BiliĢsel Kariyer Kuramı var olan kariyer geliĢim kuramları ile kavramsal
bağlar kurmaya çalıĢmaktadır. Kuram, özellikle Bandura‟nın, Genel Sosyal BiliĢsel
Kuramından ortaya çıkmıĢtır. Sosyal BiliĢsel Kariyer Kuramı Bandura‟nın üçlü
karĢılıklı nedensellik modelini benimsemektedir. Bu üçlü model, kiĢisel özelliklerin
(içsel, biliĢsel ve duygusal durumlar gibi), dıĢsal çevresel faktörlerin ve görünen
davranıĢların her birinin birbirini karĢılıklı olarak etkileyen değiĢkenler bütünü
olduğunu savunmaktadır. Sosyal BiliĢsel Kariyer Kuramı, kariyer geliĢiminin
bireysel belirleyicilerini kavramsallaĢtırmada, bireylerin kendi kariyer davranıĢını
190
düzenlemeye yardım eden birbirine bağlı öz-yeterlik inançları, sonuç beklentileri ve
kiĢisel hedefler olarak adlandırılan üç değiĢkeni vurgulamaktadır. Buna göre,
modelin üç sosyal biliĢsel mekanizmayı vurguladığı söylenebilir: (a) öz yeterlik, (b)
sonuç beklentileri ve (c) mesleki davranıĢa yönelik sosyal biliĢsel kariyer
yaklaĢımının merkezini oluĢturan kiĢisel hedefler. Bu modelde de vurgulandığı gibi,
kültürel ve kavramsal değiĢkenler kariyer karar verme sürecinde hayati bir rol
oynamaktadır. Kuram, ırk ve etnik kökeni doğrudan kiĢisel girdiler olarak gördüğü
için Sosyal BiliĢsel Kariyer modeli Afrika kökenli Amerikalılar, Asya kökenli
Amerikalılar, Ġtalyanlar ve Çinliler gibi birçok farklı kültürel gruplarla test edilmiĢtir.
Sosyal BiliĢsel Kariyer Kuramı baĢlangıcından beri oldukça dikkat çekmesine
rağmen, modelin kültürel geçerliğini test etmek için kültürlerarası ve uluslararası
alanda daha çok çalıĢmaya ihtiyaç olduğu söylenmektedir (Lent vd., 2003).
Böylelikle, bu çalıĢmanın amacı, Sosyal BiliĢsel Kariyer Kuramı‟nı temel alarak
önerilen kariyer kararsızlığı modelini Türk üniversite öğrencileri arasında sınamaktır.
ÇalıĢmanın Amacı
Bu çalıĢmanın amacı, üniversite öğrencilerinin kariyer kararsızlığını etkileyen olası
faktörleri incelemektir. Bu doğrultuda, kontrol odağı, algılanan anne baba tutumu,
kariyer karar verme öz-yeterliği ve kariyer sonuç beklentileri ile kariyer kararsızlığı
arasındaki doğrudan ve dolaylı iliĢkileri sınamak amacıyla, Sosyal BiliĢsel Kariyer
Kuramı‟na (SBKK) dayalı ara değiĢkenli nedensel bir kariyer kararsızlığı modeli
191
önerilmiĢ ve tüm bu değiĢkenlerin birleĢiminin kariyer kararsızlığını ne ölçüde
açıkladığı sınanmıĢtır.
Buna göre, Sosyal BiliĢsel Kariyer Kuramı‟na dayalı olarak önerilen kariyer
kararsızlık modelinde kariyer kararsızlığı bağımlı değiĢken olarak belirlenirken
kontrol odağı, algılanan anne baba tutumu, kariyer kararı verme öz-yeterliği ve
kariyer sonuç beklentileri bağımsız değiĢkenler olarak önerilmiĢtir. Ayrıca, önerilen
modelde, kariyer kararı verme öz-yeterliği ve kariyer sonuç beklentileri ara
değiĢkenler olarak yer almaktadır. Bu çalıĢma kapsamında, “Kariyer kararsızlığı;
kontrol odağı, algılanan anne baba tutumu (kabul/ ilgi, kontrol/ denetim, psikolojik
özerklik), kariyer kararı verme öz-yeterliği ve kariyer sonuç beklentileri tarafından
ne ölçüde yordanmaktadır?” sorusuna yanıt aranmaktadır.
Önerilen Yol Modeli
Lent vd. (1994) ilgi, seçim ve performans modellerinin tamamının sınanmasından
ziyade kısmen sınanmasını önermiĢtir. Buna göre, bu çalıĢma kapsamında önerilen
kariyer kararsızlığı modeli Sosyal BiliĢsel Kariyer Kuramı‟nın merkezi değiĢkenleri
olarak kabul edilen kiĢilik, geçmiĢe iliĢkin ortamlar (background context), öz-yeterlik
ve sonuç beklentilerini içermektedir. Bu kapsamda, kontrol odağı kariyer kararı
sürecinde güvenilir ve temel bir değiĢken olarak görüldüğünden bu çalıĢmada bir
kiĢilik değiĢkeni olarak seçilmiĢtir. Bireyler sıklıkla kariyer kararı hakkında aile
üyelerinden yardım istemektedirler. Bu nedenle kariyer kararı verme sürecinde
192
ailenin özelliklede anne babanın rolünü anlamak ve belirlemek oldukça önemlidir.
Anne ve babanın kariyer karar verme sürecindeki etkisi dikkate alındığında anne
baba tutumları bir değiĢken olarak bu çalıĢmaya dahil edilmiĢtir. Sosyal BiliĢsel
Kariyer Kuramında temel ara değiĢkenler olarak tanımlanan öz-yeterlik ve sonuç
beklentileri, bu çalıĢmada önerilen modelde de ara değiĢkenler olarak yer almaktadır.
Önerilen yol modelinde, kontrol odağı, algılanan anne baba tutumları (kabul/ ilgi,
kontrol/ denetim, psikolojik özerklik), kariyer kararı verme öz-yeterliği ve kariyer
sonuç beklentileri bağımsız değiĢkenler olarak, kariyer kararsızlığı ise bağımlı
değiĢken olarak çalıĢmada yer almıĢtır. Özellikle, kariyer kararı verme öz-yeterliği
ve kariyer sonuç beklentileri, kontrol odağı, anne baba tutumları ve kariyer
kararsızlığı arasında ara değiĢkenler olarak sınanmıĢtır (ġekil 1.2).
ÇalıĢmanın Önemi
Çoğu kiĢilik ve kariyer geliĢim kuramcısı tarafından vurgulandığı gibi, lise ve
sonraki yıllar öğrencilerin kendileri ve iĢ dünyası hakkında bilgi topladıkları bir keĢif
dönemi olarak görülmektedir. Super‟a (1980) göre bu dönem 14 ile 25 yaĢları
arasında yer alır.
193
Türkiye‟de eğitim sisteminde öğrenciler kariyerleri hakkındaki kararları lise
yıllarında vermek zorundadırlar. Bu sistemde, karar verme süreci iki aĢamada
gerçekleĢmektedir. Ġlk aĢama lise 10. sınıfta gerçekleĢen alan seçimidir. Bu seçimle
beraber öğrenciler üniversitede okuyabilecekleri olası programların sınırlarını
belirlemektedirler. Ġkinci aĢama ise,üniversite giriĢ sınavıdır. Üniversiteye girmek
isteyen aday sayısı ile gerçekte üniversiteye yerleĢen öğrenci sayısı arasındaki fark
oldukça fazladır. Her yıl adayların sadece üçte biri üniversitelerin bir lisans
programına yerleĢtirilmektedir. Bu zorlu üniversiteye giriĢ sınavına hazırlık dönemi
boyunca öğrenciler ve aileleri kariyer keĢif dönemini göz ardı etmekte ve keĢif
dönemi ile ilgili aktivitelerle yeterince ilgilenememektedir. Ancak, öğrencilerin bir
üniversitenin lisans programına yerleĢtikten sonra bulundukları programı
değiĢtirmeleri oldukça zordur. ġu anki yükseköğretim sistemi kararsız öğrencilerin
program ya da bölümlerini değiĢtirmelerine yönelik yeterince fırsat tanımadığından
üniversitelerin lisans programlarına yerleĢen birçok öğrenci istedikleri programlara
girmek için üniversite giriĢ sınavına tekrar girmektedir. Örneğin, 2010 yılında bu
sınava girenlerin % 23‟ü bir üniversitenin lisans programına kayıtlı oldukları halde
sınava tekrar girmiĢlerdir. Dolayısıyla, üniversiteye giriĢ sınavında elde edilen baĢarı,
öğrencilerin kariyer kararlarından memnun olmalarını tek baĢına sağlayamamaktadır.
ġu anki üniversiteye yerleĢtirme sisteminde, üniversite öğrencilerinin ne derece olası
erken, olgunlaĢmamıĢ ve istenmeyen seçimlerin sonuçları ile baĢbaĢa kaldığı
bilinmemektedir. Bu bakımdan lisans düzeyinde kariyer kararsızlığına etki eden
194
faktörleri değerlendirmek önemlidir. Aksi takdirde, kariyer kararsızlığının uzun
süreli bir sonucu olarak çoğu öğrenci lisans eğitimi sonunda sahip olacağı meslekten
memnun olmama riski ile karĢı karĢıya kalabilir.
Bu çalıĢma, Türkiye de üniversite öğrencilerinde kariyer kararsızlığı ile iliĢkili olan
değiĢkenleri Sosyal BiliĢsel Kariyer Kuramının seçim modelini temel alarak
araĢtırmayı amaçlamaktadır. Bu çalıĢmanın amaçlarından biri de çalıĢma kapsamında
veri toplama aracı olarak kullanılan Kariyer Karar Ölçeği, Kariyer Karar Verme Öz-
Yeterlik Ölçeği Kısa Formu ve Kariyer Sonuç Beklentileri Ölçeği‟nin çeviri, geçerlik
ve güvenirlik çalıĢmalarını yapmaktır.
Saka ve Gati (2007) tarafından da ifade edildiği gibi bireylerin kariyer kararı verme
güçlüklerinin nedenlerini değerlendirmek ve tanımlamak bu bireylere yardım
etmeden önceki ilk aĢamadır. Kariyer ilgili problemler çoğunlukla da kariyer
kararsızlığı göz ardı edildiğinde ya da psikolojik danıĢma sürecinde etkili bir Ģekilde
baĢ edilmediğinde, ciddi psikiyatrik sorunlara ya da mesleki konularda problemlere
yol açmaktadır. Örneğin, önceki çalıĢmalar depresyon ve kariyer kararsızlığı arasında
anlamlı düzeyde pozitif bir iliĢki rapor etmiĢlerdir (Saunders vd., 2000). Dolayısıyla,
üniversitelerin danıĢma merkezleri, kariyer planlama merkezleri ve akademik
bölümler öğrencilerin yaĢadığı kariyer kararsızlığının altında yatan nedenlere iliĢkin
daha kapsamlı bir anlayıĢ geliĢtirmeye ihtiyaç duymaktadır. Bu kapsamda bu
çalıĢmanın bulgularının üniversitelerin psikolojik danıĢma merkezlerinde ve
195
üniversitelerin kariyer merkezlerinde çalıĢanlara kariyer kararsızlığını önleyici ve
iyileĢtirici programlar ve uygulamalar planlamada daha fazla içgörü ve anlayıĢ
kazandırması umulmaktadır.
YÖNTEM
Örneklem
Bu çalıĢmaya, Orta Doğu Teknik Üniversitesi‟nde 2009- 2010 akademik yılında 5
ayrı fakültesinde 4 farklı sınıf düzeyinde eğitimlerine devam eden 723 (338 kız; 383
erkek; 2 cinsiyet belirtilmemiĢ) lisans öğrencisi katılmıĢtır. Öğrencilerin yaĢ
ortalaması 21.39 (SS = 1.5) olarak bulunmuĢtur. Katılımcıların, 225‟i (% 31.1)
birinci sınıf, 160‟ı (% 22.1) ikinci sınıf, 169‟u (% 23.4) üçüncü sınıf, 167‟si (% 23.1)
dördüncü sınıf öğrencileridir.
Veri Toplama Araçları
AraĢtırma kapsamında Demografik Bilgi Formu, Kariyer Karar Ölçeği, Kariyer
Kararı Öz-Yeterlik Ölçeği Kısa Formu, Kariyer Sonuç Beklentileri Ölçeği, Anne-
Baba Tutum Ölçeği ve Rotter Ġç-DıĢ Kontrol Odağı Ölçeği veri toplama araçları
olarak kullanılmıĢtır.
Demografik Bilgi Formu katılımcılara ait yaĢ, cinsiyet, genel akademik ortalama,
fakülte, sınıf ve bölümlerine iliĢkin sorulardan oluĢmaktadır.
196
Kariyer Karar Ölçeği (Osipow vd., 1976) uluslararası kariyer kararsızlık
çalıĢmalarında sıklıkla kullanılan, birçok farklı dile çevrilmiĢ, geçerlik ve güvenirlik
çalıĢmaları yapılmıĢ ölçeklerden biridir (Osipow & Winer, 1996). Ölçek, son
maddesi açık uçlu olmak üzere toplam 19 maddeden oluĢmaktadır. Ġlk iki madde
kesinlik alt ölçeğini (Certainty Subscale), geri kalan 16 madde ise (3-18) kariyer
kararsızlık alt ölçeğini (Career Indecision Subscale) oluĢturmaktadır. Kariyer
kararsızlık alt ölçeğine iliĢkin yapılan faktör analizi çalıĢmaları farklı sonuçlar
göstermiĢtir. Bu nedenle, Osipow (1987) kariyer kararsızlığının değerlendirilmesinde
kariyer kararsızlık alt ölçeğininin toplam puanın kullanılmasını önermektedir.
Kariyer Karar Ölçeği‟nin Türkçe‟ ye çevirisi, geçerlik ve güvenirlik çalıĢmaları bu
araĢtırma kapsamında gerçekleĢtirilmiĢtir. Bu amaca yönelik olarak, 336 ODTÜ
öğrencisi ile bir pilot uygulama yapılmıĢtır. Kariyer kararsızlık alt ölçeğinin faktör
yapısı literatürle tutarlı olarak maddelerin birden fazla faktöre yüklendiği ve faktör
yapısının net bir Ģekilde ayrıĢmadığı bir yapı sergilemiĢtir. Bu nedenle, Türk
örneklemi için kariyer kararsızlık alt ölçeği toplam puanı kullanılmıĢtır. Ayrıca ölçüt
geçerliğinin sınanması için ölçek KiĢisel Kararsızlık Ölçeği (Bacanlı, 2000) ile
birlikte pilot çalıĢma dıĢında ayrı bir grup öğrenciye (n = 123) uygulanmıĢtır. KiĢisel
Kararsızlık Ölçeği ve Kariyer Kararsızlık alt boyutu ile arasındaki iliĢki katsayısı .61,
kesinlik alt ölçeği ile arasındaki iliĢki katsayısı -.34 olarak bulunmuĢtur. Ġç tutarlılık
katsayısı kariyer kararsızlık alt ölçeği için .86, kesinlik alt ölçeği için .85‟dir. Ayrıca,
test-tekrar test iliĢkisel katsayısı kariyer kararsızlık alt ölçeği için .84, kesinlik alt
197
ölçeği için .77 olarak hesaplanmıĢtır. Tüm bu bulgular ıĢığında Kariyer Karar
Ölçeği‟nin Türk örnekleminde kullanılabilir olduğu söylenebilir.
Kariyer Kararı Öz-yeterlik Ölçeği Kısa-Formu Betz, Klein ve Taylor (1996)
tarafından ölçeğin ilk formundan 25 maddenin atılmasıyla oluĢturulmuĢtur. KiĢinin
kariyer kararı vermek için gerekli görevleri baĢarı ile tamamlayabileceğine ne derece
inandığını ölçmek amacı ile geliĢtirilmiĢtir. Ölçeğin kısa formu 25 maddeden
oluĢmaktadır. Ölçeğin yapı geçerliğine iliĢkin farklı araĢtırmacılar tarafından faktör
analizi çalıĢmaları yapılmıĢ ancak farklı sonuçlar bulunmuĢ ve teorikte önerilen beĢ
faktörlü yapı doğrulanamamıĢtır. Bu nedenle, kariyer kararı verme öz-yeterliğin
değerlendirilmesinde toplam puanın kullanılması önerilmektedir (Betz vd., 1996;
Taylor & Popma, 1990). Ölçeğin içsel tutarlığına iliĢkin katsayı .94, test-tekrar test
güvenirlik katsayısı ise .83 olarak rapor edilmiĢtir (Betz vd., 1996; Luzzo, 1993).
Ölçeği‟nin Türkçe‟ ye çevirisi, geçerlik ve güvenirlik çalıĢmaları bu araĢtırma
kapsamında gerçekleĢtirilmiĢtir. Bu amaca yönelik olarak, 481 ODTÜ öğrencisi ile
bir pilot uygulama yapılmıĢtır. Kariyer Kararı Verme Öz-yeterlik ölçeğinin faktör
yapısı literatürle tutarlı olarak maddelerin birden fazla faktöre yüklendiği ve faktör
yapısının net bir Ģekilde ayrıĢmadığı bir yapı sergilemiĢtir. Bu nedenle, Türk
örneklemi için kariyer kararı verme öz-yeterliğin ölçülmesinde ölçeğin toplam puanı
kullanılmıĢtır. Ayrıca, ölçüt geçerliğinin sınanması için ölçek Genel Öz-Yeterlik
Ölçeği (Jerusalem & Schwarzer, 1981) ile birlikte pilot çalıĢma dıĢında ayrı bir grup
198
öğrenciye (n = 125) uygulanmıĢtır. Ġki ölçeğin toplam puanları arasındaki iliĢki
katsayısı .65 bulunmuĢtur. Ölçeğe iliĢkin iç tutarlılık katsayısı .92‟dir. Ayrıca, test-
tekrar test iliĢkisel katsayısı .91 olarak hesaplanmıĢtır. Türk örnekleminde yapılan
geçerlik ve güvenirlik çalıĢmaları neticesinde Kariyer Kararı Öz-yeterlik Ölçeği‟nin
Türk örnekleminde kullanılabilir olduğu söylenebilir.
Kariyer Sonuç Beklentileri ve Açıklayıcı Amaçlar Ölçeği Betz ve Klein-Voyten
(1997) tarafından kariyer sonuç beklentileri, akademik sonuç beklentileri ve
açıklayıcı amaçların ölçülmesi amacıyla geliĢtirilmiĢtir. Ölçek, toplam 14 maddeden
ve akademik sonuç beklentileri (5 madde), kariyer sonuç beklentileri (4 madde) ve
açıklayıcı amaçlar (4 madde) adlı üç alt ölçekten oluĢmaktadır. Ġçsel tutarlık katsayısı
akademik sonuç beklentileri için .77, kariyer sonuç beklentileri için .79 ve açıklayıcı
amaçlar için .73 olarak rapor edilmiĢtir (Betz & Klein-Voyten, 1997).
Kariyer Sonuç Beklentileri ve Açıklayıcı Amaçlar Ölçeği‟nin Türkçe‟ ye çevirisi,
geçerlik ve güvenirlik çalıĢmaları bu çalıĢma kapsamında gerçekleĢtirilmiĢtir. Bu
amaca yönelik olarak, 303 ODTÜ öğrencisi ile bir pilot uygulama yapılmıĢtır.
Yapılan faktör analizi Kariyer Sonuç Beklentileri ve Açıklayıcı Amaçlar Ölçeği‟nin
orijinal çalıĢması ile tutarlı bir faktör yapısına sahip olduğunu göstermiĢtir. Buna
göre, ölçek kariyer sonuç beklentileri, akademik sonuç beklentileri ve açıklayıcı
amaçlar adlı üç ayrı alt ölçeğe ayrılmaktadır. ÇalıĢma kapsamında sadece kariyer
sonuç beklentileri alt ölçeği kullanılmıĢtır. Alt ölçeğe iliĢkin iç tutarlılık katsayısı .81
199
olarak bulunmuĢtur. Ayrıca, alt ölçeğe iliĢkin test-tekrar test iliĢkisel katsayısı .76
olarak hesaplanmıĢtır. Sonuç olarak, Kariyer Sonuç Beklentileri ve Açıklayıcı
Amaçlar Ölçeği‟nin Türk örnekleminde yapılan geçerlik ve güvenirlik çalıĢmaları
ölçeğin Türk örnekleminde kullanılabilir olduğuna iĢaret etmektedir.
Anne-Baba Tutum Ölçeği Lamborn vd. (1991) tarafından algılanan anne baba
tutumlarını değerlendirmek amacıyla geliĢtirilmiĢ Yılmaz (2000) tarafından Türkçe
çeviri, geçerlik ve güvenirlik çalıĢmaları yapılmıĢtır. Ölçek toplam 26 maddeden ve
kabul/ ilgi (9 madde), kontrol/ denetim (8 madde) ve psikolojik özerklik (9 madde)
adlı üç alt ölçekten oluĢmaktadır. Yılmaz (2000) tarafından alt ölçeklere iliĢkin iç
tutarlılık katsayısı kabul/ ilgi için .79, kontrol/ denetim için .85 ve psikolojik özerklik
için .67 olarak rapor edilmiĢtir.
Rotter İç-Dış Kontrol Odağı Ölçeği Rotter (1966) tarafından genellenmiĢ kontrol
beklentilerinin içsellik-dıĢsallık boyutu üzerindeki konumunu değerlendirmek için
geliĢtirilmiĢtir. Toplam 29 maddeden oluĢan ölçeğin 6 maddesi dolgu madde
olduğundan puanlanmaz. Ölçeğin Türkçe geçerlik ve güvenirlik çalıĢmaları Dağ
(1991) tarafından yapılmıĢtır. Ölçeğin Türkçe formuna iliĢkin iç tutarlık katsayısı
.71, test-tekrar test güvenirlik katsayısı ise .83 olarak rapor edilmiĢtir (Dağ, 1991).
200
Veri toplama süreci (ĠĢlem)
AraĢtırmanın verileri, Orta Doğu Teknik Üniversitesi Ġnsan AraĢtırmaları Etik
Kurulu‟ndan alınan izinin ardından, 2009-2010 akademik yılı bahar döneminde
araĢtırmacı tarafından öğretim elemanlarının izni ile sınıf ortamında toplanmıĢtır.
Tüm öğrenciler çalıĢmaya gönüllü olarak katılmıĢtır.
Verilerin analizi
Önerilen modeli sınamak ve modelde ele alınan değiĢkenlerin kariyer kararsızlığını
ne ölçüde yordadığını belirlemek amacıyla elde edilen verilere AMOS 18 veri analiz
paket programı kullanılarak yol analizi (path analysis) uygulanmıĢtır.
BULGULAR
Bu çalıĢmada ilk olarak, çalıĢmanın temel analizi olan yol analizine iliĢkin sayıltılar
test edilmiĢtir. Buna göre öncelikle veri setinde yer alan eksik veriler ve aykırı
değerler tespit edilmiĢ ve %5‟in üzerinde eksik veri bulunan 8 katılımcı veri setinden
çıkarılmıĢtır. Aykırı değerlerin tespit edilmesinde standardize edilmiĢ z puanı ve
Mahalonobis uzaklık değeri kullanılmıĢtır. Buna göre 11 katılımcı çoklu aykırı
değere sahip olduğu için veri setinden çıkarılmıĢtır. Bununla birlikte verilerin
dağılımının normal olup olmadığını test etmek için skewness ve kurtosis değerlerine
bakılmıĢ ve değerlerin önerilen değer aralığında yer aldığı anlaĢılmıĢtır.
201
Verilerin analizinde ilk olarak çalıĢmada yer alan demografik değiĢkenler (cinsiyet,
sınıf, fakülte, yaĢ ve akademik baĢarı) ile kariyer kararsızlığı arasındaki iliĢkilerin
incelenmesi amacı ile tek yönlü varyans analizi, t-testi ve Pearson Moment
korelasyonları hesaplanmıĢtır. Buna göre, t-testi cinsiyetler arasında kariyer
kararsızlığı bakımından anlamlı bir fark olmadığını göstermiĢtir. Sınıf ve kariyer
kararsızlığı arasındaki iliĢkiyi incelemek için tek yönlü varyans analizi yapılmıĢtır.
ANOVA sonuçları katılımcıların kariyer kararsızlıklarının sınıflarına göre anlamlı
bir Ģekilde farklılaĢtığını göstermiĢtir. Buna göre birinci sınıf ve son sınıf
öğrencilerinin kariyer kararsızlık puanları arasında anlamlı bir fark bulunmuĢtur.
Sonuçlar, birinci sınıf öğrencilerinin son sınıf öğrencilerine göre daha fazla
kararsızlık yaĢadığına iĢaret etmektedir. Bir diğer ANOVA sonucuna göre ise,
fakülteler açısından öğrencilerin kariyer kararsızlık puanları arasında anlamlı bir
farklılık bulunmamıĢtır.
YaĢ ve kariyer kararsızlık puanları arasındaki iliĢkinin incelenmesi için iki değiĢken
arasındaki korelasyon hesaplanmıĢ ve yaĢ ile kariyer kararsızlığı arasında negatif
yönde anlamlı bir iliĢki bulunmuĢtur. Buna göre yaĢ arttıkça kariyer kararsızlığının
azaldığı söylenebilir. Benzer olarak, akademik baĢarı ile kariyer kararsızlığı arasında
negatif yönde bir korelasyon hesaplanmıĢtır. Buna göre baĢarılı öğrencilerin daha
kararlı olduğu söylenebilir.
202
Demografik değiĢkenlerin analizleri sonrasında ise betimsel istatistik yöntemleri ile
değiĢkenlere ait ortalama ve standart sapma değerleri hesaplanmıĢ ve değiĢkenler
arasındaki korelasyonlar özetlenmiĢtir (Tablo 4.2). Buna göre kariyer kararsızlığı ile
diğer değiĢkenler arasındaki korelasyon katsayılarını incelediğimizde en büyük
korelasyon katsayısının kariyer karar verme öz-yeterliği, en düĢük ve anlamlı
korelasyon katsayısının ise algılanan anne baba tutumlarından kabul/ ilgi alt boyutu
arasında olduğu görülmüĢtür.
Genel olarak, korelasyon analizi sonuçları beklendiği gibi kariyer kararsızlığı,
kariyer kararı verme öz-yeterliği, algılanan anne baba tutumlarından kabul/ ilgi alt
boyutu ve algılanan anne baba tutumlarından psikolojik özerklik alt boyutu ile
negatif yönde; kontrol odağı ile pozitif yönde iliĢkilidir. Ancak, korelasyon analizi
sonuçları kariyer kararsızlığı ile kariyer sonuç beklentileri arasında anlamlı bir iliĢki
göstermemektedir.
Bağımsız değiĢkenlerin bağımlı değiĢkeni yordama gücünü sınamak ve kariyer kararı
verme öz-yeterliği ve kariyer sonuç beklentileri değiĢkenlerinin ara değiĢken
(mediator) olma rollerinin incelenmesi amacı ile iki farklı yol analizi (path analysis)
yapılmıĢtır. Yol analizleri AMOS 18 programı kullanılarak gerçekleĢtirilmiĢtir.
203
Önerilen modelde, kontrol odağı, kariyer kararı verme öz-yeterliği ve kariyer sonuç
beklentileri ile kariyer kararsızlığı arasındaki direk iliĢkiler; kontrol odağı, algılanan
anne baba tutumlarından kabul/ ilgi, kontrol/ denetim ve psikolojik özerklik ile
kariyer kararı verme öz-yeterliği arasındaki doğrudan iliĢkiler; kontrol odağı,
algılanan anne baba tutumları (kabul/ ilgi, kontrol/ denetim ve psikolojik özerklik) ile
kariyer sonuç beklentileri arasındaki doğrudan iliĢkiler; kariyer kararı verme öz-
yeterliği ile kariyer sonuç beklentileri arasındaki doğru iliĢki; kontrol odağı,
algılanan anne baba tutumları (kabul/ ilgi, kontrol/ denetim ve psikolojik özerklik) ile
kariyer kararı verme öz-yeterliğinin kariyer kararsızlığı ile dolaylı iliĢkileri
sınanmıĢtır (Figür 1.2).
Önerilen modelin sınanması amacı ile ilk olarak modelin çalıĢma verilerine uygun
olup olmadığını görmek için çeĢitli uygunluk ölçütleri hesaplanmıĢtır (Tablo 4.4).
Buna göre, önerilen modelin değerine ( (723) = 48.31) iliĢkin p değerinin anlamlı
olduğu görülmüĢtür. Model, ve serbestlik derecesi oranına ( = 48.31 / 3 =
16.1) göre değerlendirildiğinde ise, elde edilen sonucun önerilen 3 değerinin (Kline,
1998) üzerinde olduğu görülmüĢtür. Bununla birlikte diğer uyum indeksleri
değerlendirilmiĢ (GFI =.98; CFI = .91; TLI = .39; NFI = .91; RMSEA = .15) ve
sonuç olarak modelin eldeki veriler ile tam olarak uyum sağlamadığı anlaĢılmıĢtır.
Buna göre analiz sonuçları kontrol odağından kariyer sonuç beklentilerine giden
yolun, algılanan anne baba tutumlarından kontrol/ denetimden kariyer kararı verme
öz-yeterliğine giden yolun, yine algılanan anne baba tutumlarından kontrol/
204
denetimden kariyer sonuç beklentilerine giden yolun ve algılanan anne baba
tutumlarından psikolojik özerklikten kariyer sonuç beklentilerine giden yolun
analizden çıkarılması ve algılanan anne baba tutumlarından psikolojik özerklikten
kariyer kararsızlığına giden yeni bir yolun modele eklenmesine iliĢkin öneriler
vermiĢtir. Modele iliĢkin değiĢiklik önerileri dikkate alınarak gerçekleĢtirilmiĢ ve yol
analizi tekrarlanmıĢtır.
Buna göre, yenilenen modelde değerine ( (723) =.382) iliĢkin p değerinin anlamlı
olmadığı ve uyum indeksleri açısından ( = .382 / 3 = .13; GFI =1.00; CFI =
1.00; TLI = 1.00; NFI = 1.00; RMSEA = .00) uyumun mükemmel olduğu
anlaĢılmıĢtır. Ayrıca modeldeki tüm yolların anlamlı olduğu görülmüĢtür. Buna göre,
modeldeki doğrudan ve dolaylı yollar incelendiğinde kontrol odağının kariyer
kararsızlığı ile doğrudan iliĢkisinin (β = .07, p < .05) ve kariyer karar verme öz-
yetkinliği üzerinden dolaylı iliĢkisinin (β = .09, p < .01) anlamlı düzeyde olduğu
görülmüĢtür. Algılanan anne-baba tutumlarından kabul/ ilgi alt boyutunun kariyer
kararsızlığı ile hem kariyer karar verme öz yeterliği (β = -.10, p < .01) hem de
kariyer sonuç beklentileri (β = .03, p < .01) üzerinden dolaylı iliĢkisinin anlamlı
olduğu bulunmuĢtur. Ancak, algılanan anne-baba tutumlarından kontrol/ denetim alt
boyutunun ara değiĢkenler ve bağımlı değiĢken ile iliĢkisinin anlamlı olmadığı
dikkati çekmiĢ ve bunun sonucunda da algılanan kontrol/ denetim değiĢkeni
modelden çıkarılmıĢtır. Psikolojik özerklik anne baba tutumu alt boyutunun kariyer
kararsızlığı ile doğrudan (β = -.22, p < .001) ve kariyer kararı verme öz-yeterliği
205
üzerinden (β = -.05, p < .01) dolaylı iliĢkisinin anlamlı olduğu tespit edilmiĢtir.
Önerilen modelin ara değiĢkenlerinden kariyer kararı verme öz-yeterliğinin hem
doğrudan (β = -.48, p < .001) hem de kariyer sonuç beklentileri üzerinden dolaylı
iliĢkisinin (β = .03, p < .01) anlamlı olduğu görülmüĢtür. Diğer bir ara değiĢken olan
kariyer sonuç beklentilerinin ise kariyer kararsızlığı le doğrudan iliĢkisi (β = .14, p <
.001) anlamlı bulunmuĢtur. Tüm doğrudan ve dolaylı iliĢkiler dikkate alındığında
önerilen modelin üniversite öğrencilerinde kariyer kararsızlığının %32‟sini açıkladığı
görülmektedir.
TARTIġMA
Bu çalıĢmanın amacı Sosyal BiliĢsel Kariyer Kuramı çerçevesinde belirlenen
değiĢkenlerin Türk üniversite öğrencilerinin kariyer kararsızlığını ne ölçüde
yordadığını araĢtırmaktır. Bu kapsamda, kontrol odağı, algılanan anne baba tutumu
(kabul/ ilgi, kontrol/ denetim, psikolojik özerklik), kariyer kararı verme öz-yeterliği
ve kariyer sonuç beklentilerinin hem kariyer kararsızlığı ile hem de kendi aralarında
ne düzeyde iliĢkili oldukları incelenmiĢ ve ġekil 1.2‟de görülen ara değiĢkenli bir
model test edilmiĢtir.
Kariyer seçimi ve geliĢimi literatürü, üniversite öğrencilerinin kariyer kararsızlığına
katkıda bulunan çok sayıda faktör tanımlamaktadır. Sosyal BiliĢsel Kariyer
Kuramı‟nı üniversite öğrencileri ile sınayan çok sayıda çalıĢma olmasına rağmen
206
Türkiye‟de bu çalıĢmanın değiĢkenleri arasındaki çoklu iliĢkileri inceleyen baĢka bir
çalıĢmaya rastlanılmamıĢtır.
Kariyer kararsızlığı ile iliĢkili olarak cinsiyet, yaĢ, sınıf, ve akademik baĢarı en sık
sınanan demografik değiĢkenlerdir. Bu çalıĢmanın sonuçları kız ve erkek
öğrencilerin kariyer kararsızlığı puanları arasında önemli bir fark ortaya
koymamıĢtır. Bu nedenle, önerilen model tüm örneklem grubunda sınanmıĢtır.
Önceki çalıĢmalarla benzer olarak bu çalıĢmada da yaĢ ve kariyer kararsızlığı
arasında anlamlı düzeyde negatif bir iliĢki bulunmuĢtur. Buna göre yaĢı daha genç
öğrenciler daha fazla kariyer kararsızlığı yaĢamaktadır. Sınıf bakımından ise yaĢla
paralel olarak birinci sınıf ile son sınıf öğrencileri arasında anlamlı düzeyde negatif
bir iliĢki bulunmuĢtur. Buna göre birinci sınıf öğrencilerinin kariyer kararsızlığı
ortalama puanları son sınıf öğrencilerinin puanlarından anlamlı düzeyde daha
yüksektir. Bu çalıĢma, akademik baĢarı ve kariyer kararsızlığı arasında negatif bir
iliĢki ortaya koymuĢtur. Literatürde kariyer kararsızlığı ve akademik baĢarı
arasındaki iliĢkiye iliĢkin farklı sonuçlar rapor edilmiĢtir. Ayrıca, çalıĢma bulguları
farklı fakültelere kayıtlı öğrencilerin kariyer kararsızlığı puanları arasında anlamlı
düzeyde bir fark görülmemiĢtir.
Bu çalıĢmada kariyer kararsızlığının çoklu yordayıcılarını ve ara değiĢkenlerini
içeren bir kariyer kararsızlığı modeli önerilmektedir. Önerilen modelin sınanmasında
yol analizi kullanılmıĢtır. Analiz sonuçları önerilen modelin toplanan veri tarafından
207
desteklendiğini göstermektedir. Yol analizi sonucunda, modeli geliĢtirmek için bazı
değiĢiklikler önerilmiĢtir. Buna göre bazı istatistiksel olarak anlamlı olmayan yollar
modelden çıkarılmıĢ ve önemli bulunan bir yol modele eklenmiĢtir. Sonrasında,
düzenlenen modeli sınamak için yol analizi tekrarlanmıĢtır. Düzenlenen modelin
analiz sonuçları incelendiğinde veriye mükemmel uyum sağladığı anlaĢılmıĢtır.
ÇalıĢma bulguları kontrol odağı ile kariyer kararsızlığı arasındaki doğrudan ve
dolaylı iliĢkileri doğrular niteliktedir. Buna göre kontrol odağı ile kariyer kararsızlığı
arasında önceki çalıĢmalarla paralel olarak küçük ama pozitif bir iliĢki vardır.
ÇalıĢma bulguları ayrıca algılanan anne baba tutumlarından kabul ilgi ile kariyer
kararsızlığı arasında hem kariyer kararı verme öz-yeterliği üzerinden hem de kariyer
sonuç beklentileri üzerinden dolaylı iliĢkilere iĢaret etmektedir. Bununla birlikte,
algılanan anne baba tutumlarından psikolojik özerklik kariyer kararsızlığı ile hem
doğrudan hem de kariyer kararı verme öz-yeterliği üzerinden dolaylı olarak
iliĢkilidir. ÇalıĢma kapsamında önerilen modelde kariyer kararı verme öz-yeterliği
kariyer kararsızlığı ile hem dolaylı hem de doğrudan iliĢkili bulunmuĢtur. Ayrıca
kariyer sonuç beklentileri de kariyer kararsızlığı ie anlamlı düzeyde doğrudan iliĢkili
bulunmuĢtur.
Bu çalıĢma kapsamında Sosyal BiliĢsel Kariyer Kuramı‟na (Lent vd., 1994) dayalı
olarak önerilen kariyer kararsızlığı modeli kısmi olarak sınanmıĢtır. Bu çalıĢmanın
bulguları kontrol odağı ve algılanan anne baba tutumlarının Sosyal BiliĢsel Kariyer
208
Kuramı‟nda önerildiği gibi öğrencilerin kariyer kararsızlığı ile doğrudan ve kariyer
kararı verme öz-yeterliği üzerinden dolaylı bir Ģekilde iliĢkili olduğunu göstermiĢtir.
Öz-yeterlik önceki Sosyal BiliĢsel Kariyer Kuramı‟nı test etme çalıĢmalarında en sık
incelenen ve ara değiĢken özelliği genellikle doğrulanan değiĢkenlerden birisidir.
Elde edilen sonuçlar Sosyal BiliĢsel Kariyer Kuramı‟yla (Lent vd., 1994) paralel
olarak, kariyer karar verme öz-yeterliğinin kontrol odağı, algılanan kabul/ ilgi ve
algılanan psikolojik özerklik değiĢkenleri ile kariyer kararsızlığı arasında önemli bir
ara değiĢken olduğunu doğrular niteliktedir. Diğer bir deyiĢle, önceki çalıĢmalarda
olduğu gibi bu çalıĢmada kapsamında da öz-yeterliğin ara değiĢken olma rolü
doğrulanmıĢtır. Huang (1999) ve Wallace ve Kindaichi‟e (2005) benzer olarak anne
babaya ait değiĢkenler önerilen modelde kariyer kararsızlığı ile doğrudan ve dolaylı
olarak iliĢkili görünmektedir bu da Sosyal BiliĢsel Kariyer Kuramı‟na dayalı
geliĢtirilen hipotezleri doğrular niteliktedir. Ayrıca, Lent vd. (1994) önerdiği ve Feldt
ve Woelfel‟in (2009) desteklediği gibi sonuç beklentileri kariyer kararsızlığının
anlamlı yordayıcılarından birisi olmuĢtur. Bu çalıĢmada önerilen model kariyer
kararsızlığına ait toplam varyansın %32 sini açıklamaktadır ve bu oran önceki model
test etme çalıĢmaları ile yakın görünmektedir. Örneğin, Weiss (2000) kariyer kararı
verme öz-yeterliği, kariyer sonuç beklentileri ve algılanan bariyerler ya da engelleri
dahil ettiği model test etme çalıĢmasında tüm bu değiĢkenlerin kariyer kararsızlığının
%37‟sini açıkladığını rapor etmiĢtir.
Bu araĢtırma, Türkiyede‟ki üniversite öğrencilerinin kariyer kararsızlığına iliĢkin
Sosyal BiliĢsel Kariyer Kuramı‟nı test eden ilk çalıĢma olması açısında önem
209
taĢımaktadır. Bu çalıĢmanın bulgularına dayanarak bundan sonra ülkemizde
yapılacak çalıĢmalar için bazı öneriler yapılabilir. Bu çalıĢma kapsamında kariyer
kararsızlığına iliĢkin yeniden düzenlenen model tarafından açıklanan toplam varyans
küçük olmamasına rağmen varyansın geri kalanı çalıĢmaya dahil edilmemiĢ diğer
değiĢkenlerle açıklanabilir. ġüphesiz, bu çalıĢmanın kapsamı dıĢında kalan ancak
üniversite öğrencilerinin kariyer kararsızlığı ile anlamlı bir Ģekilde iliĢkili olabilecek
birçok değiĢken vardır. Bunların gelecek çalıĢmalarda dikkate alınması önerilebilir.
Bu çalıĢmada veriler tek bir devlet üniversitesinden toplanmıĢtır. Bu kapsamda
çalıĢmada sınanan modelin farklı bölgelerde yer alan üniversitelerden elde edilen
farklı örneklem gruplarında sınanması önerilebilir.
Bu çalıĢmanın tek bağımlı değiĢkeni olan kariyer kararsızlığı sadece genel düzeyde
ölçülmüĢtür. Ancak, öğrencilerin hepsi aynı tip kariyer kararsızlığı yaĢamamaktadır.
Buna göre gelecekteki çalıĢmalarda kronik ya da geliĢimsel gibi adlandırılan farklı
tiplerdeki kariyer kararsızlığı incelenerek öğrencilerin yaĢadıkları kariyer
kararsızlığına iliĢkin daha detaylı bilgi sahibi olunabilir.
Bunlara ek olarak, çalıĢma bulguları, kariyer kararsızlığının en güçlü yordayıcısının
kariyer kararı verme öz-yeterliği olduğunu göstermiĢtir. Buna göre, kariyer
kararsızlığının üstesinden gelinmesi doğrultusunda çalıĢmalar yapan araĢtırmacıların
210
ya da psikolojik danıĢmanların öğrencilerin kariyer kararsızlığını azaltmak için
öncellikle onların kariyer kararı verme öz-yeterlik düzeylerini belirlemeleri
önerilebilir.
211
APPENDIX H
CURRICULUM VITAE
PERSONAL INFORMATION
Surname, Name: Büyükgöze Kavas, AyĢenur
Nationality: Turkish (TC)
Date and Place of Birth: 12 April 1981, Samsun
Marital Status: Married with two children
Phone: +90 312 210 4029
Fax: +90 312 210 79 67
Email: [email protected]
EDUCATION
Degree Institution Year of Graduation
BS Hacettepe University,
Department of Educational
Sciences
2003
WORK EXPERIENCE
Year Place Enrollment
2004- Present METU, Department of
Educational Sciences
Research Assistant
2009 University of Florida,
Department of Psychology
Visiting Scholar
FOREIGN LANGUAGES
Advanced English
212
SELECTED PUBLICATIONS
1. Büyükgöze-Kavas, A. (In press). Bireysel ve grupla psikolojik danıĢma
uygulamalarına yönelik bir değerlendirme. Türk Eğitim Bilimleri Dergisi.
2. Neimeyer, G. J., Taylor, J. M., Wear, D. M., & Buyukgoze-Kavas, A. (2011).
How special are the specialties?: Workplace settings in counseling and
clinical psychology in the United States. The Counselling Psychology
Quarterly, 24, 43-53.
3. Buyukgoze-Kavas, A., Taylor, J. M., Neimeyer, G. J., & Yerin Güneri, O.
(2010). The mentoring relationship: A comparison of counseling students in
the United States of America and Turkey. The Counselling Psychology
Quarterly, 23, 387-398.
4. Aksoy-Toska, G., Neimeyer, G. J., Taylor, J. M., Buyukgoze-Kavas, A., &
Rice, K. G. (2010). Epistemology and allegiance: Exploring the role of
therapists‟ epistemic commitments on psychotherapy outcomes. European
Journal of Psychotherapy and Counselling, 12, 65-75.
5. Büyükgöze-Kavas, A. (2009). Self-esteem and health risk behaviors among
Turkish late adolescents. Adolescence, 44, 187-198.
213
6. Büyükgöze-Kavas, A. & Bugay, A. (2009). Öğretmen adaylarının hizmet
öncesi eğitimlerinde gördükleri eksiklikler ve çözüm önerileri. Pamukkale
Üniversitesi Eğitim Fakültesi Dergisi, 25, 13-21.
7. Yerin Güneri, O., Büyükgöze-Kavas, A., & Koydemir, S. (2007). Okul
psikolojik danıĢmanlarının profesyonel geliĢimi: Acemilikten olgunlaĢmaya
giden zorlu yol. In D. Owen, F. Korkut-Owen, & R. Özyürek (Eds.), Gelişen
psikolojik danışma ve rehberlik: Meslekleşme sürecindeki ilerlemeler, cilt I
(pp. 139-162). Ankara: Nobel.
8. Büyükgöze-Kavas, A. (2007). Eating attitudes and depression in a Turkish
sample. European Eating Disorders Review, 15, 305-310.
9. Bugay, A., Büyükgöze-Kavas, A., & Demir, A. (2007). Acculturative stress
of international students. The International Journal of Interdisciplinary
Social Sciences, 2 (4), 33-38.
10. Büyükgöze-Kavas, A. (2005). Eğitim fakültesi öğrencilerinin aldıkları
mesleki rehberlik hizmetleri ve mesleklerini değiĢtirmek isteme düzeylerinin
bazı değiĢkenler açısından incelenmesi. Marmara Üniversitesi Atatürk Eğitim
Fakültesi Eğitim Bilimleri Dergisi, 21, 111–122.
